Overview

Dataset statistics

Number of variables62
Number of observations116
Missing cells2865
Missing cells (%)39.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory56.3 KiB
Average record size in memory497.1 B

Variable types

Numeric13
Categorical41
Unsupported8

Alerts

airdate has constant value "2020-12-16" Constant
_embedded.show.network.officialSite has constant value "https://www.bbc.co.uk/bbcthree" Constant
_embedded.show.dvdCountry.name has constant value "Ukraine" Constant
_embedded.show.dvdCountry.code has constant value "UA" Constant
_embedded.show.dvdCountry.timezone has constant value "Europe/Zaporozhye" Constant
url has a high cardinality: 116 distinct values High cardinality
name has a high cardinality: 106 distinct values High cardinality
_links.self.href has a high cardinality: 116 distinct values High cardinality
_embedded.show.url has a high cardinality: 72 distinct values High cardinality
_embedded.show.name has a high cardinality: 72 distinct values High cardinality
_embedded.show.premiered has a high cardinality: 58 distinct values High cardinality
_embedded.show.officialSite has a high cardinality: 63 distinct values High cardinality
_embedded.show.image.medium has a high cardinality: 68 distinct values High cardinality
_embedded.show.image.original has a high cardinality: 68 distinct values High cardinality
_embedded.show.summary has a high cardinality: 61 distinct values High cardinality
_embedded.show._links.self.href has a high cardinality: 72 distinct values High cardinality
_embedded.show._links.previousepisode.href has a high cardinality: 72 distinct values High cardinality
id is highly correlated with rating.average and 4 other fieldsHigh correlation
season is highly correlated with rating.average and 3 other fieldsHigh correlation
number is highly correlated with _embedded.show.rating.average and 1 other fieldsHigh correlation
runtime is highly correlated with rating.average and 2 other fieldsHigh correlation
rating.average is highly correlated with id and 9 other fieldsHigh correlation
_embedded.show.id is highly correlated with id and 5 other fieldsHigh correlation
_embedded.show.runtime is highly correlated with runtime and 2 other fieldsHigh correlation
_embedded.show.averageRuntime is highly correlated with runtime and 2 other fieldsHigh correlation
_embedded.show.rating.average is highly correlated with id and 4 other fieldsHigh correlation
_embedded.show.weight is highly correlated with rating.average and 2 other fieldsHigh correlation
_embedded.show.webChannel.id is highly correlated with rating.average and 2 other fieldsHigh correlation
_embedded.show.externals.tvrage is highly correlated with id and 10 other fieldsHigh correlation
_embedded.show.externals.thetvdb is highly correlated with season and 4 other fieldsHigh correlation
_embedded.show.updated is highly correlated with rating.average and 2 other fieldsHigh correlation
_embedded.show.network.id is highly correlated with id and 7 other fieldsHigh correlation
id is highly correlated with rating.average and 3 other fieldsHigh correlation
season is highly correlated with number and 3 other fieldsHigh correlation
number is highly correlated with season and 3 other fieldsHigh correlation
runtime is highly correlated with _embedded.show.runtime and 1 other fieldsHigh correlation
rating.average is highly correlated with id and 6 other fieldsHigh correlation
_embedded.show.id is highly correlated with rating.average and 3 other fieldsHigh correlation
_embedded.show.runtime is highly correlated with season and 4 other fieldsHigh correlation
_embedded.show.averageRuntime is highly correlated with runtime and 2 other fieldsHigh correlation
_embedded.show.rating.average is highly correlated with id and 6 other fieldsHigh correlation
_embedded.show.weight is highly correlated with rating.average and 2 other fieldsHigh correlation
_embedded.show.webChannel.id is highly correlated with _embedded.show.rating.average and 2 other fieldsHigh correlation
_embedded.show.externals.tvrage is highly correlated with id and 10 other fieldsHigh correlation
_embedded.show.externals.thetvdb is highly correlated with rating.average and 3 other fieldsHigh correlation
_embedded.show.updated is highly correlated with _embedded.show.rating.average and 1 other fieldsHigh correlation
_embedded.show.network.id is highly correlated with id and 6 other fieldsHigh correlation
id is highly correlated with _embedded.show.externals.tvrage and 1 other fieldsHigh correlation
season is highly correlated with rating.average and 2 other fieldsHigh correlation
number is highly correlated with _embedded.show.rating.average and 1 other fieldsHigh correlation
runtime is highly correlated with _embedded.show.runtime and 1 other fieldsHigh correlation
rating.average is highly correlated with season and 7 other fieldsHigh correlation
_embedded.show.id is highly correlated with rating.average and 3 other fieldsHigh correlation
_embedded.show.runtime is highly correlated with runtime and 2 other fieldsHigh correlation
_embedded.show.averageRuntime is highly correlated with runtime and 2 other fieldsHigh correlation
_embedded.show.rating.average is highly correlated with number and 3 other fieldsHigh correlation
_embedded.show.weight is highly correlated with rating.average and 2 other fieldsHigh correlation
_embedded.show.webChannel.id is highly correlated with rating.average and 2 other fieldsHigh correlation
_embedded.show.externals.tvrage is highly correlated with id and 10 other fieldsHigh correlation
_embedded.show.externals.thetvdb is highly correlated with season and 3 other fieldsHigh correlation
_embedded.show.updated is highly correlated with rating.average and 1 other fieldsHigh correlation
_embedded.show.network.id is highly correlated with id and 5 other fieldsHigh correlation
id is highly correlated with airstamp and 27 other fieldsHigh correlation
season is highly correlated with number and 21 other fieldsHigh correlation
number is highly correlated with season and 34 other fieldsHigh correlation
type is highly correlated with airtime and 21 other fieldsHigh correlation
airtime is highly correlated with number and 36 other fieldsHigh correlation
airstamp is highly correlated with id and 40 other fieldsHigh correlation
runtime is highly correlated with season and 39 other fieldsHigh correlation
summary is highly correlated with id and 33 other fieldsHigh correlation
rating.average is highly correlated with runtime and 23 other fieldsHigh correlation
image.medium is highly correlated with id and 39 other fieldsHigh correlation
image.original is highly correlated with id and 39 other fieldsHigh correlation
_embedded.show.id is highly correlated with id and 39 other fieldsHigh correlation
_embedded.show.url is highly correlated with id and 44 other fieldsHigh correlation
_embedded.show.name is highly correlated with id and 44 other fieldsHigh correlation
_embedded.show.type is highly correlated with season and 40 other fieldsHigh correlation
_embedded.show.language is highly correlated with id and 40 other fieldsHigh correlation
_embedded.show.status is highly correlated with number and 34 other fieldsHigh correlation
_embedded.show.runtime is highly correlated with season and 35 other fieldsHigh correlation
_embedded.show.averageRuntime is highly correlated with season and 41 other fieldsHigh correlation
_embedded.show.premiered is highly correlated with id and 44 other fieldsHigh correlation
_embedded.show.ended is highly correlated with id and 33 other fieldsHigh correlation
_embedded.show.officialSite is highly correlated with id and 44 other fieldsHigh correlation
_embedded.show.schedule.time is highly correlated with number and 36 other fieldsHigh correlation
_embedded.show.rating.average is highly correlated with type and 28 other fieldsHigh correlation
_embedded.show.weight is highly correlated with id and 36 other fieldsHigh correlation
_embedded.show.webChannel.id is highly correlated with id and 32 other fieldsHigh correlation
_embedded.show.webChannel.name is highly correlated with id and 41 other fieldsHigh correlation
_embedded.show.webChannel.officialSite is highly correlated with id and 34 other fieldsHigh correlation
_embedded.show.externals.tvrage is highly correlated with number and 21 other fieldsHigh correlation
_embedded.show.externals.thetvdb is highly correlated with season and 33 other fieldsHigh correlation
_embedded.show.externals.imdb is highly correlated with id and 43 other fieldsHigh correlation
_embedded.show.image.medium is highly correlated with id and 44 other fieldsHigh correlation
_embedded.show.image.original is highly correlated with id and 44 other fieldsHigh correlation
_embedded.show.summary is highly correlated with id and 43 other fieldsHigh correlation
_embedded.show.updated is highly correlated with id and 31 other fieldsHigh correlation
_embedded.show._links.self.href is highly correlated with id and 44 other fieldsHigh correlation
_embedded.show._links.previousepisode.href is highly correlated with id and 44 other fieldsHigh correlation
_embedded.show.webChannel.country.name is highly correlated with season and 36 other fieldsHigh correlation
_embedded.show.webChannel.country.code is highly correlated with season and 36 other fieldsHigh correlation
_embedded.show.webChannel.country.timezone is highly correlated with season and 36 other fieldsHigh correlation
_embedded.show._links.nextepisode.href is highly correlated with id and 35 other fieldsHigh correlation
_embedded.show.network.id is highly correlated with id and 30 other fieldsHigh correlation
_embedded.show.network.name is highly correlated with id and 38 other fieldsHigh correlation
_embedded.show.network.country.name is highly correlated with id and 35 other fieldsHigh correlation
_embedded.show.network.country.code is highly correlated with id and 35 other fieldsHigh correlation
_embedded.show.network.country.timezone is highly correlated with id and 35 other fieldsHigh correlation
number has 2 (1.7%) missing values Missing
runtime has 10 (8.6%) missing values Missing
summary has 81 (69.8%) missing values Missing
rating.average has 108 (93.1%) missing values Missing
image.medium has 80 (69.0%) missing values Missing
image.original has 80 (69.0%) missing values Missing
_embedded.show.language has 6 (5.2%) missing values Missing
_embedded.show.runtime has 46 (39.7%) missing values Missing
_embedded.show.averageRuntime has 6 (5.2%) missing values Missing
_embedded.show.ended has 51 (44.0%) missing values Missing
_embedded.show.officialSite has 16 (13.8%) missing values Missing
_embedded.show.rating.average has 106 (91.4%) missing values Missing
_embedded.show.network has 116 (100.0%) missing values Missing
_embedded.show.webChannel.id has 3 (2.6%) missing values Missing
_embedded.show.webChannel.name has 3 (2.6%) missing values Missing
_embedded.show.webChannel.country has 116 (100.0%) missing values Missing
_embedded.show.webChannel.officialSite has 31 (26.7%) missing values Missing
_embedded.show.dvdCountry has 116 (100.0%) missing values Missing
_embedded.show.externals.tvrage has 111 (95.7%) missing values Missing
_embedded.show.externals.thetvdb has 42 (36.2%) missing values Missing
_embedded.show.externals.imdb has 62 (53.4%) missing values Missing
_embedded.show.image.medium has 4 (3.4%) missing values Missing
_embedded.show.image.original has 4 (3.4%) missing values Missing
_embedded.show.summary has 11 (9.5%) missing values Missing
image has 116 (100.0%) missing values Missing
_embedded.show.webChannel.country.name has 69 (59.5%) missing values Missing
_embedded.show.webChannel.country.code has 69 (59.5%) missing values Missing
_embedded.show.webChannel.country.timezone has 69 (59.5%) missing values Missing
_embedded.show._links.nextepisode.href has 109 (94.0%) missing values Missing
_embedded.show.network.id has 106 (91.4%) missing values Missing
_embedded.show.network.name has 106 (91.4%) missing values Missing
_embedded.show.network.country.name has 106 (91.4%) missing values Missing
_embedded.show.network.country.code has 106 (91.4%) missing values Missing
_embedded.show.network.country.timezone has 106 (91.4%) missing values Missing
_embedded.show.network.officialSite has 115 (99.1%) missing values Missing
_embedded.show.webChannel has 116 (100.0%) missing values Missing
_embedded.show.image has 116 (100.0%) missing values Missing
_embedded.show.dvdCountry.name has 115 (99.1%) missing values Missing
_embedded.show.dvdCountry.code has 115 (99.1%) missing values Missing
_embedded.show.dvdCountry.timezone has 115 (99.1%) missing values Missing
url is uniformly distributed Uniform
name is uniformly distributed Uniform
summary is uniformly distributed Uniform
image.medium is uniformly distributed Uniform
image.original is uniformly distributed Uniform
_links.self.href is uniformly distributed Uniform
_embedded.show._links.nextepisode.href is uniformly distributed Uniform
_embedded.show.network.name is uniformly distributed Uniform
_embedded.show.network.country.name is uniformly distributed Uniform
_embedded.show.network.country.code is uniformly distributed Uniform
_embedded.show.network.country.timezone is uniformly distributed Uniform
id has unique values Unique
url has unique values Unique
_links.self.href has unique values Unique
_embedded.show.genres is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.schedule.days is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.network is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.webChannel.country is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.dvdCountry is an unsupported type, check if it needs cleaning or further analysis Unsupported
image is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.webChannel is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.image is an unsupported type, check if it needs cleaning or further analysis Unsupported

Reproduction

Analysis started2022-09-05 04:40:15.052003
Analysis finished2022-09-05 04:40:32.087406
Duration17.04 seconds
Software versionpandas-profiling v3.2.0
Download configurationconfig.json

Variables

id
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
UNIQUE

Distinct116
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2031864.078
Minimum1945146
Maximum2386107
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2022-09-04T23:40:32.137406image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum1945146
5-th percentile1963088
Q11984952.75
median1987998.5
Q32047460
95-th percentile2197362
Maximum2386107
Range440961
Interquartile range (IQR)62507.25

Descriptive statistics

Standard deviation86935.73115
Coefficient of variation (CV)0.04278619427
Kurtosis3.125651342
Mean2031864.078
Median Absolute Deviation (MAD)10537
Skewness1.836016252
Sum235696233
Variance7557821351
MonotonicityNot monotonic
2022-09-04T23:40:32.234406image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
21796131
 
0.9%
19870331
 
0.9%
19975091
 
0.9%
19975081
 
0.9%
19880631
 
0.9%
19880621
 
0.9%
19879991
 
0.9%
19879981
 
0.9%
19879971
 
0.9%
19879961
 
0.9%
Other values (106)106
91.4%
ValueCountFrequency (%)
19451461
0.9%
19458681
0.9%
19459001
0.9%
19459011
0.9%
19585741
0.9%
19588671
0.9%
19644951
0.9%
19702061
0.9%
19720271
0.9%
19760401
0.9%
ValueCountFrequency (%)
23861071
0.9%
23300071
0.9%
23181061
0.9%
22059751
0.9%
22059741
0.9%
21975961
0.9%
21972841
0.9%
21926241
0.9%
21820831
0.9%
21796131
0.9%

url
Categorical

HIGH CARDINALITY
UNIFORM
UNIQUE

Distinct116
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
https://www.tvmaze.com/episodes/2179613/kontakty-1x30-kontakty-v-telefone-ili-makarova-ruslan-belyj-guram-amaran-andrej-beburisvili-sasa-vas
 
1
https://www.tvmaze.com/episodes/1987033/the-expanse-aftershow-1x01-naren-shankar
 
1
https://www.tvmaze.com/episodes/1997509/the-penalty-zone-1x02-episode-2
 
1
https://www.tvmaze.com/episodes/1997508/the-penalty-zone-1x01-episode-1
 
1
https://www.tvmaze.com/episodes/1988063/forever-love-1x12-episode-12
 
1
Other values (111)
111 

Length

Max length161
Median length113
Mean length81.79310345
Min length62

Characters and Unicode

Total characters9488
Distinct characters40
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique116 ?
Unique (%)100.0%

Sample

1st rowhttps://www.tvmaze.com/episodes/2179613/kontakty-1x30-kontakty-v-telefone-ili-makarova-ruslan-belyj-guram-amaran-andrej-beburisvili-sasa-vas
2nd rowhttps://www.tvmaze.com/episodes/1983259/mertvye-dusi-1x03-seria-3
3rd rowhttps://www.tvmaze.com/episodes/1983260/mertvye-dusi-1x04-seria-4
4th rowhttps://www.tvmaze.com/episodes/1997413/wan-sheng-jie-2x12-ah-goodbye-friends
5th rowhttps://www.tvmaze.com/episodes/2386107/xian-feng-jian-yu-lu-1x48-episode-48

Common Values

ValueCountFrequency (%)
https://www.tvmaze.com/episodes/2179613/kontakty-1x30-kontakty-v-telefone-ili-makarova-ruslan-belyj-guram-amaran-andrej-beburisvili-sasa-vas1
 
0.9%
https://www.tvmaze.com/episodes/1987033/the-expanse-aftershow-1x01-naren-shankar1
 
0.9%
https://www.tvmaze.com/episodes/1997509/the-penalty-zone-1x02-episode-21
 
0.9%
https://www.tvmaze.com/episodes/1997508/the-penalty-zone-1x01-episode-11
 
0.9%
https://www.tvmaze.com/episodes/1988063/forever-love-1x12-episode-121
 
0.9%
https://www.tvmaze.com/episodes/1988062/forever-love-1x11-episode-111
 
0.9%
https://www.tvmaze.com/episodes/1987999/rompan-todo-la-historia-del-rock-en-america-latina-1x06-una-nueva-era1
 
0.9%
https://www.tvmaze.com/episodes/1987998/rompan-todo-la-historia-del-rock-en-america-latina-1x05-un-solo-continente1
 
0.9%
https://www.tvmaze.com/episodes/1987997/rompan-todo-la-historia-del-rock-en-america-latina-1x04-rock-en-tu-idioma1
 
0.9%
https://www.tvmaze.com/episodes/1987996/rompan-todo-la-historia-del-rock-en-america-latina-1x03-musica-a-colores1
 
0.9%
Other values (106)106
91.4%

Length

2022-09-04T23:40:32.342406image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://www.tvmaze.com/episodes/2179613/kontakty-1x30-kontakty-v-telefone-ili-makarova-ruslan-belyj-guram-amaran-andrej-beburisvili-sasa-vas1
 
0.9%
https://www.tvmaze.com/episodes/1977324/stjernestov-1x16-episode-161
 
0.9%
https://www.tvmaze.com/episodes/1983260/mertvye-dusi-1x04-seria-41
 
0.9%
https://www.tvmaze.com/episodes/1997413/wan-sheng-jie-2x12-ah-goodbye-friends1
 
0.9%
https://www.tvmaze.com/episodes/2386107/xian-feng-jian-yu-lu-1x48-episode-481
 
0.9%
https://www.tvmaze.com/episodes/2095628/yi-nian-yong-heng-1x21-episode-211
 
0.9%
https://www.tvmaze.com/episodes/2096298/no-turning-back-romance-1x04-41
 
0.9%
https://www.tvmaze.com/episodes/2030020/dolls-frontline-2x12-episode-121
 
0.9%
https://www.tvmaze.com/episodes/2066369/chu-feng-yi-dian-shizi-1x06-episode-61
 
0.9%
https://www.tvmaze.com/episodes/2071481/youths-in-the-breeze-1x11-people-from-the-story-031
 
0.9%
Other values (106)106
91.4%

Most occurring characters

ValueCountFrequency (%)
e812
 
8.6%
-760
 
8.0%
t582
 
6.1%
/580
 
6.1%
s566
 
6.0%
o523
 
5.5%
a430
 
4.5%
w389
 
4.1%
i386
 
4.1%
m354
 
3.7%
Other values (30)4106
43.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter6498
68.5%
Decimal Number1302
 
13.7%
Other Punctuation928
 
9.8%
Dash Punctuation760
 
8.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e812
12.5%
t582
 
9.0%
s566
 
8.7%
o523
 
8.0%
a430
 
6.6%
w389
 
6.0%
i386
 
5.9%
m354
 
5.4%
p351
 
5.4%
d271
 
4.2%
Other values (16)1834
28.2%
Decimal Number
ValueCountFrequency (%)
1313
24.0%
9171
13.1%
0152
11.7%
2147
11.3%
898
 
7.5%
395
 
7.3%
793
 
7.1%
683
 
6.4%
476
 
5.8%
574
 
5.7%
Other Punctuation
ValueCountFrequency (%)
/580
62.5%
.232
 
25.0%
:116
 
12.5%
Dash Punctuation
ValueCountFrequency (%)
-760
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin6498
68.5%
Common2990
31.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
e812
12.5%
t582
 
9.0%
s566
 
8.7%
o523
 
8.0%
a430
 
6.6%
w389
 
6.0%
i386
 
5.9%
m354
 
5.4%
p351
 
5.4%
d271
 
4.2%
Other values (16)1834
28.2%
Common
ValueCountFrequency (%)
-760
25.4%
/580
19.4%
1313
10.5%
.232
 
7.8%
9171
 
5.7%
0152
 
5.1%
2147
 
4.9%
:116
 
3.9%
898
 
3.3%
395
 
3.2%
Other values (4)326
10.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII9488
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e812
 
8.6%
-760
 
8.0%
t582
 
6.1%
/580
 
6.1%
s566
 
6.0%
o523
 
5.5%
a430
 
4.5%
w389
 
4.1%
i386
 
4.1%
m354
 
3.7%
Other values (30)4106
43.3%

name
Categorical

HIGH CARDINALITY
UNIFORM

Distinct106
Distinct (%)91.4%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
Episode 21
 
3
Episode 2
 
2
Episode 12
 
2
Episode 13
 
2
Episode 14
 
2
Other values (101)
105 

Length

Max length97
Median length72
Mean length17.88793103
Min length1

Characters and Unicode

Total characters2075
Distinct characters131
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique97 ?
Unique (%)83.6%

Sample

1st rowКОНТАКТЫ в телефоне Ильи Макарова: Руслан Белый, Гурам Амарян, Андрей Бебуришвили, Саша Ваш
2nd rowСерия 3
3rd rowСерия 4
4th rowAh, Goodbye Friends
5th rowEpisode 48

Common Values

ValueCountFrequency (%)
Episode 213
 
2.6%
Episode 22
 
1.7%
Episode 122
 
1.7%
Episode 132
 
1.7%
Episode 142
 
1.7%
Episode 62
 
1.7%
Episode 82
 
1.7%
Episode 222
 
1.7%
Episode 52
 
1.7%
Rock en tu idioma1
 
0.9%
Other values (96)96
82.8%

Length

2022-09-04T23:40:32.445405image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
episode43
 
11.5%
the12
 
3.2%
9
 
2.4%
a5
 
1.3%
24
 
1.1%
163
 
0.8%
la3
 
0.8%
43
 
0.8%
213
 
0.8%
from2
 
0.5%
Other values (263)288
76.8%

Most occurring characters

ValueCountFrequency (%)
259
 
12.5%
e160
 
7.7%
o113
 
5.4%
i109
 
5.3%
s89
 
4.3%
a87
 
4.2%
d73
 
3.5%
n69
 
3.3%
r65
 
3.1%
E57
 
2.7%
Other values (121)994
47.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1321
63.7%
Uppercase Letter346
 
16.7%
Space Separator259
 
12.5%
Decimal Number105
 
5.1%
Other Punctuation36
 
1.7%
Dash Punctuation4
 
0.2%
Math Symbol2
 
0.1%
Open Punctuation1
 
< 0.1%
Close Punctuation1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e160
 
12.1%
o113
 
8.6%
i109
 
8.3%
s89
 
6.7%
a87
 
6.6%
d73
 
5.5%
n69
 
5.2%
r65
 
4.9%
t57
 
4.3%
p51
 
3.9%
Other values (51)448
33.9%
Uppercase Letter
ValueCountFrequency (%)
E57
 
16.5%
T20
 
5.8%
S17
 
4.9%
M14
 
4.0%
D14
 
4.0%
R13
 
3.8%
L12
 
3.5%
O11
 
3.2%
H11
 
3.2%
N10
 
2.9%
Other values (37)167
48.3%
Decimal Number
ValueCountFrequency (%)
124
22.9%
221
20.0%
314
13.3%
411
10.5%
010
9.5%
67
 
6.7%
86
 
5.7%
55
 
4.8%
94
 
3.8%
73
 
2.9%
Other Punctuation
ValueCountFrequency (%)
,17
47.2%
'4
 
11.1%
&3
 
8.3%
:3
 
8.3%
?3
 
8.3%
.3
 
8.3%
#2
 
5.6%
/1
 
2.8%
Space Separator
ValueCountFrequency (%)
259
100.0%
Dash Punctuation
ValueCountFrequency (%)
-4
100.0%
Math Symbol
ValueCountFrequency (%)
|2
100.0%
Open Punctuation
ValueCountFrequency (%)
(1
100.0%
Close Punctuation
ValueCountFrequency (%)
)1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1369
66.0%
Common408
 
19.7%
Cyrillic298
 
14.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
e160
 
11.7%
o113
 
8.3%
i109
 
8.0%
s89
 
6.5%
a87
 
6.4%
d73
 
5.3%
n69
 
5.0%
r65
 
4.7%
E57
 
4.2%
t57
 
4.2%
Other values (45)490
35.8%
Cyrillic
ValueCountFrequency (%)
а32
 
10.7%
е18
 
6.0%
р17
 
5.7%
н16
 
5.4%
и14
 
4.7%
о11
 
3.7%
т10
 
3.4%
в9
 
3.0%
О9
 
3.0%
К8
 
2.7%
Other values (43)154
51.7%
Common
ValueCountFrequency (%)
259
63.5%
124
 
5.9%
221
 
5.1%
,17
 
4.2%
314
 
3.4%
411
 
2.7%
010
 
2.5%
67
 
1.7%
86
 
1.5%
55
 
1.2%
Other values (13)34
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII1767
85.2%
Cyrillic298
 
14.4%
None10
 
0.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
259
 
14.7%
e160
 
9.1%
o113
 
6.4%
i109
 
6.2%
s89
 
5.0%
a87
 
4.9%
d73
 
4.1%
n69
 
3.9%
r65
 
3.7%
E57
 
3.2%
Other values (61)686
38.8%
Cyrillic
ValueCountFrequency (%)
а32
 
10.7%
е18
 
6.0%
р17
 
5.7%
н16
 
5.4%
и14
 
4.7%
о11
 
3.7%
т10
 
3.4%
в9
 
3.0%
О9
 
3.0%
К8
 
2.7%
Other values (43)154
51.7%
None
ValueCountFrequency (%)
ó3
30.0%
í2
20.0%
ø1
 
10.0%
ú1
 
10.0%
å1
 
10.0%
ç1
 
10.0%
ã1
 
10.0%

season
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct12
Distinct (%)10.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean89.25
Minimum1
Maximum2020
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2022-09-04T23:40:32.527406image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q32
95-th percentile21.25
Maximum2020
Range2019
Interquartile range (IQR)1

Descriptive statistics

Standard deviation411.5731194
Coefficient of variation (CV)4.611463523
Kurtosis19.10662937
Mean89.25
Median Absolute Deviation (MAD)0
Skewness4.558015202
Sum10353
Variance169392.4326
MonotonicityNot monotonic
2022-09-04T23:40:32.587481image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
183
71.6%
27
 
6.0%
55
 
4.3%
20205
 
4.3%
45
 
4.3%
33
 
2.6%
73
 
2.6%
101
 
0.9%
81
 
0.9%
181
 
0.9%
Other values (2)2
 
1.7%
ValueCountFrequency (%)
183
71.6%
27
 
6.0%
33
 
2.6%
45
 
4.3%
55
 
4.3%
73
 
2.6%
81
 
0.9%
101
 
0.9%
141
 
0.9%
181
 
0.9%
ValueCountFrequency (%)
20205
4.3%
311
 
0.9%
181
 
0.9%
141
 
0.9%
101
 
0.9%
81
 
0.9%
73
2.6%
55
4.3%
45
4.3%
33
2.6%

number
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct48
Distinct (%)42.1%
Missing2
Missing (%)1.7%
Infinite0
Infinite (%)0.0%
Mean26.72807018
Minimum1
Maximum343
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2022-09-04T23:40:32.662703image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13.25
median11
Q325.5
95-th percentile72.6
Maximum343
Range342
Interquartile range (IQR)22.25

Descriptive statistics

Standard deviation53.4704095
Coefficient of variation (CV)2.000533864
Kurtosis22.49976727
Mean26.72807018
Median Absolute Deviation (MAD)9
Skewness4.547885564
Sum3047
Variance2859.084692
MonotonicityNot monotonic
2022-09-04T23:40:32.742926image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
110
 
8.6%
310
 
8.6%
29
 
7.8%
46
 
5.2%
66
 
5.2%
115
 
4.3%
55
 
4.3%
84
 
3.4%
124
 
3.4%
214
 
3.4%
Other values (38)51
44.0%
ValueCountFrequency (%)
110
8.6%
29
7.8%
310
8.6%
46
5.2%
55
4.3%
66
5.2%
71
 
0.9%
84
 
3.4%
92
 
1.7%
115
4.3%
ValueCountFrequency (%)
3431
0.9%
3061
0.9%
3051
0.9%
1531
0.9%
1021
0.9%
831
0.9%
671
0.9%
631
0.9%
621
0.9%
572
1.7%

type
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
regular
114 
significant_special
 
2

Length

Max length19
Median length7
Mean length7.206896552
Min length7

Characters and Unicode

Total characters836
Distinct characters14
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowregular
2nd rowregular
3rd rowregular
4th rowregular
5th rowregular

Common Values

ValueCountFrequency (%)
regular114
98.3%
significant_special2
 
1.7%

Length

2022-09-04T23:40:32.819922image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-04T23:40:32.881926image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
regular114
98.3%
significant_special2
 
1.7%

Most occurring characters

ValueCountFrequency (%)
r228
27.3%
a118
14.1%
e116
13.9%
g116
13.9%
l116
13.9%
u114
13.6%
i8
 
1.0%
s4
 
0.5%
n4
 
0.5%
c4
 
0.5%
Other values (4)8
 
1.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter834
99.8%
Connector Punctuation2
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
r228
27.3%
a118
14.1%
e116
13.9%
g116
13.9%
l116
13.9%
u114
13.7%
i8
 
1.0%
s4
 
0.5%
n4
 
0.5%
c4
 
0.5%
Other values (3)6
 
0.7%
Connector Punctuation
ValueCountFrequency (%)
_2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin834
99.8%
Common2
 
0.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
r228
27.3%
a118
14.1%
e116
13.9%
g116
13.9%
l116
13.9%
u114
13.7%
i8
 
1.0%
s4
 
0.5%
n4
 
0.5%
c4
 
0.5%
Other values (3)6
 
0.7%
Common
ValueCountFrequency (%)
_2
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII836
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
r228
27.3%
a118
14.1%
e116
13.9%
g116
13.9%
l116
13.9%
u114
13.6%
i8
 
1.0%
s4
 
0.5%
n4
 
0.5%
c4
 
0.5%
Other values (4)8
 
1.0%

airdate
Categorical

CONSTANT
REJECTED

Distinct1
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
2020-12-16
116 

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters1160
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020-12-16
2nd row2020-12-16
3rd row2020-12-16
4th row2020-12-16
5th row2020-12-16

Common Values

ValueCountFrequency (%)
2020-12-16116
100.0%

Length

2022-09-04T23:40:32.938926image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-04T23:40:32.999847image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
2020-12-16116
100.0%

Most occurring characters

ValueCountFrequency (%)
2348
30.0%
0232
20.0%
-232
20.0%
1232
20.0%
6116
 
10.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number928
80.0%
Dash Punctuation232
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2348
37.5%
0232
25.0%
1232
25.0%
6116
 
12.5%
Dash Punctuation
ValueCountFrequency (%)
-232
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common1160
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2348
30.0%
0232
20.0%
-232
20.0%
1232
20.0%
6116
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII1160
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2348
30.0%
0232
20.0%
-232
20.0%
1232
20.0%
6116
 
10.0%

airtime
Categorical

HIGH CORRELATION

Distinct11
Distinct (%)9.5%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
80 
20:00
17 
21:00
 
6
10:00
 
4
12:00
 
2
Other values (6)
 
7

Length

Max length5
Median length0
Mean length1.551724138
Min length0

Characters and Unicode

Total characters180
Distinct characters10
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)4.3%

Sample

1st row12:00
2nd row
3rd row
4th row10:00
5th row10:00

Common Values

ValueCountFrequency (%)
80
69.0%
20:0017
 
14.7%
21:006
 
5.2%
10:004
 
3.4%
12:002
 
1.7%
00:002
 
1.7%
06:001
 
0.9%
17:351
 
0.9%
09:001
 
0.9%
08:301
 
0.9%

Length

2022-09-04T23:40:33.056925image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
20:0017
47.2%
21:006
 
16.7%
10:004
 
11.1%
12:002
 
5.6%
00:002
 
5.6%
06:001
 
2.8%
17:351
 
2.8%
09:001
 
2.8%
08:301
 
2.8%
19:001
 
2.8%

Most occurring characters

ValueCountFrequency (%)
097
53.9%
:36
 
20.0%
225
 
13.9%
114
 
7.8%
32
 
1.1%
92
 
1.1%
61
 
0.6%
71
 
0.6%
51
 
0.6%
81
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number144
80.0%
Other Punctuation36
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
097
67.4%
225
 
17.4%
114
 
9.7%
32
 
1.4%
92
 
1.4%
61
 
0.7%
71
 
0.7%
51
 
0.7%
81
 
0.7%
Other Punctuation
ValueCountFrequency (%)
:36
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common180
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
097
53.9%
:36
 
20.0%
225
 
13.9%
114
 
7.8%
32
 
1.1%
92
 
1.1%
61
 
0.6%
71
 
0.6%
51
 
0.6%
81
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII180
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
097
53.9%
:36
 
20.0%
225
 
13.9%
114
 
7.8%
32
 
1.1%
92
 
1.1%
61
 
0.6%
71
 
0.6%
51
 
0.6%
81
 
0.6%

airstamp
Categorical

HIGH CORRELATION

Distinct19
Distinct (%)16.4%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
2020-12-16T12:00:00+00:00
75 
2020-12-16T04:00:00+00:00
 
7
2020-12-16T11:00:00+00:00
 
6
2020-12-16T13:00:00+00:00
 
6
2020-12-16T02:00:00+00:00
 
3
Other values (14)
19 

Length

Max length25
Median length25
Mean length25
Min length25

Characters and Unicode

Total characters2900
Distinct characters13
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10 ?
Unique (%)8.6%

Sample

1st row2020-12-16T00:00:00+00:00
2nd row2020-12-16T00:00:00+00:00
3rd row2020-12-16T00:00:00+00:00
4th row2020-12-16T02:00:00+00:00
5th row2020-12-16T02:00:00+00:00

Common Values

ValueCountFrequency (%)
2020-12-16T12:00:00+00:0075
64.7%
2020-12-16T04:00:00+00:007
 
6.0%
2020-12-16T11:00:00+00:006
 
5.2%
2020-12-16T13:00:00+00:006
 
5.2%
2020-12-16T02:00:00+00:003
 
2.6%
2020-12-16T00:00:00+00:003
 
2.6%
2020-12-16T10:00:00+00:002
 
1.7%
2020-12-16T15:00:00+00:002
 
1.7%
2020-12-16T17:00:00+00:002
 
1.7%
2020-12-16T07:00:00+00:001
 
0.9%
Other values (9)9
 
7.8%

Length

2022-09-04T23:40:33.124849image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2020-12-16t12:00:00+00:0075
64.7%
2020-12-16t04:00:00+00:007
 
6.0%
2020-12-16t11:00:00+00:006
 
5.2%
2020-12-16t13:00:00+00:006
 
5.2%
2020-12-16t02:00:00+00:003
 
2.6%
2020-12-16t00:00:00+00:003
 
2.6%
2020-12-16t10:00:00+00:002
 
1.7%
2020-12-16t15:00:00+00:002
 
1.7%
2020-12-16t17:00:00+00:002
 
1.7%
2020-12-16t13:30:00+00:001
 
0.9%
Other values (9)9
 
7.8%

Most occurring characters

ValueCountFrequency (%)
01182
40.8%
2426
 
14.7%
:348
 
12.0%
1335
 
11.6%
-232
 
8.0%
T116
 
4.0%
+116
 
4.0%
6114
 
3.9%
310
 
0.3%
48
 
0.3%
Other values (3)13
 
0.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number2088
72.0%
Other Punctuation348
 
12.0%
Dash Punctuation232
 
8.0%
Uppercase Letter116
 
4.0%
Math Symbol116
 
4.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
01182
56.6%
2426
 
20.4%
1335
 
16.0%
6114
 
5.5%
310
 
0.5%
48
 
0.4%
56
 
0.3%
75
 
0.2%
92
 
0.1%
Other Punctuation
ValueCountFrequency (%)
:348
100.0%
Dash Punctuation
ValueCountFrequency (%)
-232
100.0%
Uppercase Letter
ValueCountFrequency (%)
T116
100.0%
Math Symbol
ValueCountFrequency (%)
+116
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common2784
96.0%
Latin116
 
4.0%

Most frequent character per script

Common
ValueCountFrequency (%)
01182
42.5%
2426
 
15.3%
:348
 
12.5%
1335
 
12.0%
-232
 
8.3%
+116
 
4.2%
6114
 
4.1%
310
 
0.4%
48
 
0.3%
56
 
0.2%
Other values (2)7
 
0.3%
Latin
ValueCountFrequency (%)
T116
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII2900
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
01182
40.8%
2426
 
14.7%
:348
 
12.0%
1335
 
11.6%
-232
 
8.0%
T116
 
4.0%
+116
 
4.0%
6114
 
3.9%
310
 
0.3%
48
 
0.3%
Other values (3)13
 
0.4%

runtime
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct39
Distinct (%)36.8%
Missing10
Missing (%)8.6%
Infinite0
Infinite (%)0.0%
Mean39.46226415
Minimum2
Maximum161
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2022-09-04T23:40:33.200848image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile5.25
Q124.25
median45
Q345
95-th percentile87.25
Maximum161
Range159
Interquartile range (IQR)20.75

Descriptive statistics

Standard deviation26.29835212
Coefficient of variation (CV)0.6664177205
Kurtosis5.708139951
Mean39.46226415
Median Absolute Deviation (MAD)12.5
Skewness1.83942547
Sum4183
Variance691.6033243
MonotonicityNot monotonic
2022-09-04T23:40:33.287848image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
4532
27.6%
305
 
4.3%
124
 
3.4%
524
 
3.4%
1204
 
3.4%
53
 
2.6%
193
 
2.6%
73
 
2.6%
263
 
2.6%
203
 
2.6%
Other values (29)42
36.2%
(Missing)10
 
8.6%
ValueCountFrequency (%)
21
 
0.9%
42
1.7%
53
2.6%
61
 
0.9%
73
2.6%
82
1.7%
111
 
0.9%
124
3.4%
131
 
0.9%
181
 
0.9%
ValueCountFrequency (%)
1611
 
0.9%
1204
3.4%
901
 
0.9%
791
 
0.9%
603
2.6%
551
 
0.9%
531
 
0.9%
524
3.4%
512
1.7%
501
 
0.9%

summary
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct35
Distinct (%)100.0%
Missing81
Missing (%)69.8%
Memory size1.0 KiB
<p>Ahead of the long awaited second series of RuPaul's Drag Race UK Mama Ru introduces the 12 fabulous new queens competing for the title of the UK's Next Drag Race Superstar. </p>
 
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<p>Ty Franck and Wes Chatham welcome Executive Producer &amp; Showrunner, Naren Shankar, to chat through how they adapted Nemesis Games to Season 5, The Churn, and what the hell a showrunner does.</p>
 
1
<p>Steven Strait (Lead Actor &amp; Producer) and Breck Eisner (Director) join Wes Chatham and Ty Franck on this episode of the official The Expanse After show to discuss the contentious relationship between writer and director, insulting Steven Spielberg, the concept of family for Belters, capturing Baltimore in a totally uncomplicated way, and the once-a-season Simpsons easter egg.</p>
 
1
Other values (30)
30 

Length

Max length595
Median length187
Mean length192.8571429
Min length91

Characters and Unicode

Total characters6750
Distinct characters78
Distinct categories9 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique35 ?
Unique (%)100.0%

Sample

1st row<p>Ahead of the long awaited second series of RuPaul's Drag Race UK Mama Ru introduces the 12 fabulous new queens competing for the title of the UK's Next Drag Race Superstar. </p>
2nd row<p>Holden tries to convince Fred Johnson to destroy the last sample of protomolecule. Naomi gets an important lead to her son. On Luna, Avasarala begins to hunt for Marco Inaros.</p>
3rd row<p>Holden and Fred deal with infiltrators on Tycho. Drummer's past comes back to haunt her. Amos returns to Baltimore. Alex and Bobbie's investigation on Mars leads to rogue soldiers.</p>
4th row<p>Naomi comes face to face with Filip. Holden and Fred turn the tables. Avasarala closes in on Marco's plot.</p>
5th row<p>How do they know you're lonely? Because you're watching this, mawmuh. Trixie and Katya explore the concept of loneliness!</p>

Common Values

ValueCountFrequency (%)
<p>Ahead of the long awaited second series of RuPaul's Drag Race UK Mama Ru introduces the 12 fabulous new queens competing for the title of the UK's Next Drag Race Superstar. </p>1
 
0.9%
<p>To get back in her family's good graces, Tumi looks for the missing best man. Against their better judgement, Tumi and Beauty seek out a family member.</p><p><br /> </p>1
 
0.9%
<p>Tumi shocks both families and devastates Beauty by letting slip a secret. But this time, after some soul searching, she decides to face the music.</p>1
 
0.9%
<p>Ty Franck and Wes Chatham welcome Executive Producer &amp; Showrunner, Naren Shankar, to chat through how they adapted Nemesis Games to Season 5, The Churn, and what the hell a showrunner does.</p>1
 
0.9%
<p>Steven Strait (Lead Actor &amp; Producer) and Breck Eisner (Director) join Wes Chatham and Ty Franck on this episode of the official The Expanse After show to discuss the contentious relationship between writer and director, insulting Steven Spielberg, the concept of family for Belters, capturing Baltimore in a totally uncomplicated way, and the once-a-season Simpsons easter egg.</p>1
 
0.9%
<p>Ty and Wes sit down with Thomas Jane, a man who wears many hats—that's not a Miller joke, he directed Episode 3 in Season 5! Watch them break down Thomas' new role as a director, diverting from the scripts, and the impact of seeing Alien (1979) as children.</p>1
 
0.9%
<p>Latin America's rock movement was sparked by Ritchie Valens' "La Bamba" and the Beatles but found its own voice in youth and resistance to dictatorship.</p><p><br /> </p>1
 
0.9%
<p>When the band Peace and Love began chanting, "We got the power!" at the first rock festival in Mexico in 1971, the government responded by banning rock.</p><p><br /> </p>1
 
0.9%
<p>After the fall of the Argentine dictatorship in 1983 and the Mexico City earthquake in 1985, rock explodes with ingenuity. And it's all in Spanish.</p><p><br /> </p>1
 
0.9%
<p>Argentina's Soda Stereo were the first all-hemispheric hitmakers, followed by Mexico's Caifanes and Los Prisioneros from Pinochet's Chile.</p><p><br /> </p>1
 
0.9%
Other values (25)25
 
21.6%
(Missing)81
69.8%

Length

2022-09-04T23:40:33.385848image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
the70
 
6.3%
and48
 
4.3%
to37
 
3.3%
of26
 
2.3%
a25
 
2.2%
in21
 
1.9%
17
 
1.5%
p17
 
1.5%
her15
 
1.3%
on11
 
1.0%
Other values (618)830
74.3%

Most occurring characters

ValueCountFrequency (%)
1065
15.8%
e590
 
8.7%
t443
 
6.6%
a413
 
6.1%
o380
 
5.6%
i350
 
5.2%
n348
 
5.2%
s328
 
4.9%
r317
 
4.7%
h233
 
3.5%
Other values (68)2283
33.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter4919
72.9%
Space Separator1082
 
16.0%
Uppercase Letter242
 
3.6%
Math Symbol230
 
3.4%
Other Punctuation215
 
3.2%
Decimal Number41
 
0.6%
Dash Punctuation15
 
0.2%
Close Punctuation3
 
< 0.1%
Open Punctuation3
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e590
12.0%
t443
 
9.0%
a413
 
8.4%
o380
 
7.7%
i350
 
7.1%
n348
 
7.1%
s328
 
6.7%
r317
 
6.4%
h233
 
4.7%
p198
 
4.0%
Other values (18)1319
26.8%
Uppercase Letter
ValueCountFrequency (%)
A32
13.2%
S27
 
11.2%
T22
 
9.1%
M17
 
7.0%
B15
 
6.2%
L14
 
5.8%
R14
 
5.8%
C13
 
5.4%
W11
 
4.5%
E9
 
3.7%
Other values (13)68
28.1%
Other Punctuation
ValueCountFrequency (%)
/66
30.7%
.55
25.6%
,54
25.1%
'23
 
10.7%
!5
 
2.3%
"4
 
1.9%
?3
 
1.4%
;2
 
0.9%
&2
 
0.9%
:1
 
0.5%
Decimal Number
ValueCountFrequency (%)
19
22.0%
97
17.1%
26
14.6%
75
12.2%
54
9.8%
04
9.8%
83
 
7.3%
32
 
4.9%
41
 
2.4%
Space Separator
ValueCountFrequency (%)
1065
98.4%
 17
 
1.6%
Math Symbol
ValueCountFrequency (%)
<115
50.0%
>115
50.0%
Dash Punctuation
ValueCountFrequency (%)
-12
80.0%
3
 
20.0%
Close Punctuation
ValueCountFrequency (%)
)3
100.0%
Open Punctuation
ValueCountFrequency (%)
(3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin5161
76.5%
Common1589
 
23.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
e590
 
11.4%
t443
 
8.6%
a413
 
8.0%
o380
 
7.4%
i350
 
6.8%
n348
 
6.7%
s328
 
6.4%
r317
 
6.1%
h233
 
4.5%
p198
 
3.8%
Other values (41)1561
30.2%
Common
ValueCountFrequency (%)
1065
67.0%
<115
 
7.2%
>115
 
7.2%
/66
 
4.2%
.55
 
3.5%
,54
 
3.4%
'23
 
1.4%
 17
 
1.1%
-12
 
0.8%
19
 
0.6%
Other values (17)58
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII6728
99.7%
None19
 
0.3%
Punctuation3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1065
15.8%
e590
 
8.8%
t443
 
6.6%
a413
 
6.1%
o380
 
5.6%
i350
 
5.2%
n348
 
5.2%
s328
 
4.9%
r317
 
4.7%
h233
 
3.5%
Other values (64)2261
33.6%
None
ValueCountFrequency (%)
 17
89.5%
é1
 
5.3%
ö1
 
5.3%
Punctuation
ValueCountFrequency (%)
3
100.0%

rating.average
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct6
Distinct (%)75.0%
Missing108
Missing (%)93.1%
Infinite0
Infinite (%)0.0%
Mean7.4125
Minimum6
Maximum8.9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2022-09-04T23:40:33.460848image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum6
5-th percentile6.175
Q16.5
median7
Q38.65
95-th percentile8.865
Maximum8.9
Range2.9
Interquartile range (IQR)2.15

Descriptive statistics

Standard deviation1.198138437
Coefficient of variation (CV)0.1616375632
Kurtosis-2.129663048
Mean7.4125
Median Absolute Deviation (MAD)0.75
Skewness0.2813067323
Sum59.3
Variance1.435535714
MonotonicityNot monotonic
2022-09-04T23:40:33.523980image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
6.53
 
2.6%
8.61
 
0.9%
8.81
 
0.9%
8.91
 
0.9%
7.51
 
0.9%
61
 
0.9%
(Missing)108
93.1%
ValueCountFrequency (%)
61
 
0.9%
6.53
2.6%
7.51
 
0.9%
8.61
 
0.9%
8.81
 
0.9%
8.91
 
0.9%
ValueCountFrequency (%)
8.91
 
0.9%
8.81
 
0.9%
8.61
 
0.9%
7.51
 
0.9%
6.53
2.6%
61
 
0.9%

image.medium
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct36
Distinct (%)100.0%
Missing80
Missing (%)69.0%
Memory size1.0 KiB
https://static.tvmaze.com/uploads/images/medium_landscape/289/723332.jpg
 
1
https://static.tvmaze.com/uploads/images/medium_landscape/289/722896.jpg
 
1
https://static.tvmaze.com/uploads/images/medium_landscape/289/722900.jpg
 
1
https://static.tvmaze.com/uploads/images/medium_landscape/289/722901.jpg
 
1
https://static.tvmaze.com/uploads/images/medium_landscape/289/722902.jpg
 
1
Other values (31)
31 

Length

Max length72
Median length72
Mean length72
Min length72

Characters and Unicode

Total characters2592
Distinct characters32
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique36 ?
Unique (%)100.0%

Sample

1st rowhttps://static.tvmaze.com/uploads/images/medium_landscape/360/901423.jpg
2nd rowhttps://static.tvmaze.com/uploads/images/medium_landscape/290/726350.jpg
3rd rowhttps://static.tvmaze.com/uploads/images/medium_landscape/289/723073.jpg
4th rowhttps://static.tvmaze.com/uploads/images/medium_landscape/288/721855.jpg
5th rowhttps://static.tvmaze.com/uploads/images/medium_landscape/300/752218.jpg

Common Values

ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/medium_landscape/289/723332.jpg1
 
0.9%
https://static.tvmaze.com/uploads/images/medium_landscape/289/722896.jpg1
 
0.9%
https://static.tvmaze.com/uploads/images/medium_landscape/289/722900.jpg1
 
0.9%
https://static.tvmaze.com/uploads/images/medium_landscape/289/722901.jpg1
 
0.9%
https://static.tvmaze.com/uploads/images/medium_landscape/289/722902.jpg1
 
0.9%
https://static.tvmaze.com/uploads/images/medium_landscape/289/722922.jpg1
 
0.9%
https://static.tvmaze.com/uploads/images/medium_landscape/289/723295.jpg1
 
0.9%
https://static.tvmaze.com/uploads/images/medium_landscape/289/723297.jpg1
 
0.9%
https://static.tvmaze.com/uploads/images/medium_landscape/360/901423.jpg1
 
0.9%
https://static.tvmaze.com/uploads/images/medium_landscape/289/722895.jpg1
 
0.9%
Other values (26)26
 
22.4%
(Missing)80
69.0%

Length

2022-09-04T23:40:33.599980image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/medium_landscape/289/723332.jpg1
 
2.8%
https://static.tvmaze.com/uploads/images/medium_landscape/289/722896.jpg1
 
2.8%
https://static.tvmaze.com/uploads/images/medium_landscape/293/734761.jpg1
 
2.8%
https://static.tvmaze.com/uploads/images/medium_landscape/290/726350.jpg1
 
2.8%
https://static.tvmaze.com/uploads/images/medium_landscape/289/723073.jpg1
 
2.8%
https://static.tvmaze.com/uploads/images/medium_landscape/288/721855.jpg1
 
2.8%
https://static.tvmaze.com/uploads/images/medium_landscape/300/752218.jpg1
 
2.8%
https://static.tvmaze.com/uploads/images/medium_landscape/370/926331.jpg1
 
2.8%
https://static.tvmaze.com/uploads/images/medium_landscape/370/926359.jpg1
 
2.8%
https://static.tvmaze.com/uploads/images/medium_landscape/289/722744.jpg1
 
2.8%
Other values (26)26
72.2%

Most occurring characters

ValueCountFrequency (%)
/252
 
9.7%
a216
 
8.3%
t180
 
6.9%
s180
 
6.9%
m180
 
6.9%
p144
 
5.6%
e144
 
5.6%
i108
 
4.2%
c108
 
4.2%
.108
 
4.2%
Other values (22)972
37.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1836
70.8%
Other Punctuation396
 
15.3%
Decimal Number324
 
12.5%
Connector Punctuation36
 
1.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a216
11.8%
t180
9.8%
s180
9.8%
m180
9.8%
p144
 
7.8%
e144
 
7.8%
i108
 
5.9%
c108
 
5.9%
d108
 
5.9%
l72
 
3.9%
Other values (8)396
21.6%
Decimal Number
ValueCountFrequency (%)
286
26.5%
848
14.8%
747
14.5%
943
13.3%
342
13.0%
018
 
5.6%
511
 
3.4%
610
 
3.1%
110
 
3.1%
49
 
2.8%
Other Punctuation
ValueCountFrequency (%)
/252
63.6%
.108
27.3%
:36
 
9.1%
Connector Punctuation
ValueCountFrequency (%)
_36
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1836
70.8%
Common756
29.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
a216
11.8%
t180
9.8%
s180
9.8%
m180
9.8%
p144
 
7.8%
e144
 
7.8%
i108
 
5.9%
c108
 
5.9%
d108
 
5.9%
l72
 
3.9%
Other values (8)396
21.6%
Common
ValueCountFrequency (%)
/252
33.3%
.108
14.3%
286
 
11.4%
848
 
6.3%
747
 
6.2%
943
 
5.7%
342
 
5.6%
_36
 
4.8%
:36
 
4.8%
018
 
2.4%
Other values (4)40
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII2592
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/252
 
9.7%
a216
 
8.3%
t180
 
6.9%
s180
 
6.9%
m180
 
6.9%
p144
 
5.6%
e144
 
5.6%
i108
 
4.2%
c108
 
4.2%
.108
 
4.2%
Other values (22)972
37.5%

image.original
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct36
Distinct (%)100.0%
Missing80
Missing (%)69.0%
Memory size1.0 KiB
https://static.tvmaze.com/uploads/images/original_untouched/289/723332.jpg
 
1
https://static.tvmaze.com/uploads/images/original_untouched/289/722896.jpg
 
1
https://static.tvmaze.com/uploads/images/original_untouched/289/722900.jpg
 
1
https://static.tvmaze.com/uploads/images/original_untouched/289/722901.jpg
 
1
https://static.tvmaze.com/uploads/images/original_untouched/289/722902.jpg
 
1
Other values (31)
31 

Length

Max length74
Median length74
Mean length74
Min length74

Characters and Unicode

Total characters2664
Distinct characters33
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique36 ?
Unique (%)100.0%

Sample

1st rowhttps://static.tvmaze.com/uploads/images/original_untouched/360/901423.jpg
2nd rowhttps://static.tvmaze.com/uploads/images/original_untouched/290/726350.jpg
3rd rowhttps://static.tvmaze.com/uploads/images/original_untouched/289/723073.jpg
4th rowhttps://static.tvmaze.com/uploads/images/original_untouched/288/721855.jpg
5th rowhttps://static.tvmaze.com/uploads/images/original_untouched/300/752218.jpg

Common Values

ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/original_untouched/289/723332.jpg1
 
0.9%
https://static.tvmaze.com/uploads/images/original_untouched/289/722896.jpg1
 
0.9%
https://static.tvmaze.com/uploads/images/original_untouched/289/722900.jpg1
 
0.9%
https://static.tvmaze.com/uploads/images/original_untouched/289/722901.jpg1
 
0.9%
https://static.tvmaze.com/uploads/images/original_untouched/289/722902.jpg1
 
0.9%
https://static.tvmaze.com/uploads/images/original_untouched/289/722922.jpg1
 
0.9%
https://static.tvmaze.com/uploads/images/original_untouched/289/723295.jpg1
 
0.9%
https://static.tvmaze.com/uploads/images/original_untouched/289/723297.jpg1
 
0.9%
https://static.tvmaze.com/uploads/images/original_untouched/360/901423.jpg1
 
0.9%
https://static.tvmaze.com/uploads/images/original_untouched/289/722895.jpg1
 
0.9%
Other values (26)26
 
22.4%
(Missing)80
69.0%

Length

2022-09-04T23:40:33.673980image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/original_untouched/289/723332.jpg1
 
2.8%
https://static.tvmaze.com/uploads/images/original_untouched/289/722896.jpg1
 
2.8%
https://static.tvmaze.com/uploads/images/original_untouched/293/734761.jpg1
 
2.8%
https://static.tvmaze.com/uploads/images/original_untouched/290/726350.jpg1
 
2.8%
https://static.tvmaze.com/uploads/images/original_untouched/289/723073.jpg1
 
2.8%
https://static.tvmaze.com/uploads/images/original_untouched/288/721855.jpg1
 
2.8%
https://static.tvmaze.com/uploads/images/original_untouched/300/752218.jpg1
 
2.8%
https://static.tvmaze.com/uploads/images/original_untouched/370/926331.jpg1
 
2.8%
https://static.tvmaze.com/uploads/images/original_untouched/370/926359.jpg1
 
2.8%
https://static.tvmaze.com/uploads/images/original_untouched/289/722744.jpg1
 
2.8%
Other values (26)26
72.2%

Most occurring characters

ValueCountFrequency (%)
/252
 
9.5%
t216
 
8.1%
a180
 
6.8%
s144
 
5.4%
o144
 
5.4%
i144
 
5.4%
m108
 
4.1%
u108
 
4.1%
e108
 
4.1%
g108
 
4.1%
Other values (23)1152
43.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1908
71.6%
Other Punctuation396
 
14.9%
Decimal Number324
 
12.2%
Connector Punctuation36
 
1.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t216
 
11.3%
a180
 
9.4%
s144
 
7.5%
o144
 
7.5%
i144
 
7.5%
m108
 
5.7%
u108
 
5.7%
e108
 
5.7%
g108
 
5.7%
c108
 
5.7%
Other values (9)540
28.3%
Decimal Number
ValueCountFrequency (%)
286
26.5%
848
14.8%
747
14.5%
943
13.3%
342
13.0%
018
 
5.6%
511
 
3.4%
610
 
3.1%
110
 
3.1%
49
 
2.8%
Other Punctuation
ValueCountFrequency (%)
/252
63.6%
.108
27.3%
:36
 
9.1%
Connector Punctuation
ValueCountFrequency (%)
_36
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1908
71.6%
Common756
 
28.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
t216
 
11.3%
a180
 
9.4%
s144
 
7.5%
o144
 
7.5%
i144
 
7.5%
m108
 
5.7%
u108
 
5.7%
e108
 
5.7%
g108
 
5.7%
c108
 
5.7%
Other values (9)540
28.3%
Common
ValueCountFrequency (%)
/252
33.3%
.108
14.3%
286
 
11.4%
848
 
6.3%
747
 
6.2%
943
 
5.7%
342
 
5.6%
_36
 
4.8%
:36
 
4.8%
018
 
2.4%
Other values (4)40
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII2664
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/252
 
9.5%
t216
 
8.1%
a180
 
6.8%
s144
 
5.4%
o144
 
5.4%
i144
 
5.4%
m108
 
4.1%
u108
 
4.1%
e108
 
4.1%
g108
 
4.1%
Other values (23)1152
43.2%

_links.self.href
Categorical

HIGH CARDINALITY
UNIFORM
UNIQUE

Distinct116
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
https://api.tvmaze.com/episodes/2179613
 
1
https://api.tvmaze.com/episodes/1987033
 
1
https://api.tvmaze.com/episodes/1997509
 
1
https://api.tvmaze.com/episodes/1997508
 
1
https://api.tvmaze.com/episodes/1988063
 
1
Other values (111)
111 

Length

Max length39
Median length39
Mean length39
Min length39

Characters and Unicode

Total characters4524
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique116 ?
Unique (%)100.0%

Sample

1st rowhttps://api.tvmaze.com/episodes/2179613
2nd rowhttps://api.tvmaze.com/episodes/1983259
3rd rowhttps://api.tvmaze.com/episodes/1983260
4th rowhttps://api.tvmaze.com/episodes/1997413
5th rowhttps://api.tvmaze.com/episodes/2386107

Common Values

ValueCountFrequency (%)
https://api.tvmaze.com/episodes/21796131
 
0.9%
https://api.tvmaze.com/episodes/19870331
 
0.9%
https://api.tvmaze.com/episodes/19975091
 
0.9%
https://api.tvmaze.com/episodes/19975081
 
0.9%
https://api.tvmaze.com/episodes/19880631
 
0.9%
https://api.tvmaze.com/episodes/19880621
 
0.9%
https://api.tvmaze.com/episodes/19879991
 
0.9%
https://api.tvmaze.com/episodes/19879981
 
0.9%
https://api.tvmaze.com/episodes/19879971
 
0.9%
https://api.tvmaze.com/episodes/19879961
 
0.9%
Other values (106)106
91.4%

Length

2022-09-04T23:40:33.877979image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://api.tvmaze.com/episodes/21796131
 
0.9%
https://api.tvmaze.com/episodes/19773241
 
0.9%
https://api.tvmaze.com/episodes/19832601
 
0.9%
https://api.tvmaze.com/episodes/19974131
 
0.9%
https://api.tvmaze.com/episodes/23861071
 
0.9%
https://api.tvmaze.com/episodes/20956281
 
0.9%
https://api.tvmaze.com/episodes/20962981
 
0.9%
https://api.tvmaze.com/episodes/20300201
 
0.9%
https://api.tvmaze.com/episodes/20663691
 
0.9%
https://api.tvmaze.com/episodes/20714811
 
0.9%
Other values (106)106
91.4%

Most occurring characters

ValueCountFrequency (%)
/464
 
10.3%
p348
 
7.7%
s348
 
7.7%
e348
 
7.7%
t348
 
7.7%
o232
 
5.1%
a232
 
5.1%
i232
 
5.1%
.232
 
5.1%
m232
 
5.1%
Other values (16)1508
33.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2900
64.1%
Other Punctuation812
 
17.9%
Decimal Number812
 
17.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
p348
12.0%
s348
12.0%
e348
12.0%
t348
12.0%
o232
8.0%
a232
8.0%
i232
8.0%
m232
8.0%
h116
 
4.0%
d116
 
4.0%
Other values (3)348
12.0%
Decimal Number
ValueCountFrequency (%)
9161
19.8%
1147
18.1%
781
10.0%
881
10.0%
273
9.0%
067
8.3%
658
 
7.1%
551
 
6.3%
350
 
6.2%
443
 
5.3%
Other Punctuation
ValueCountFrequency (%)
/464
57.1%
.232
28.6%
:116
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin2900
64.1%
Common1624
35.9%

Most frequent character per script

Common
ValueCountFrequency (%)
/464
28.6%
.232
14.3%
9161
 
9.9%
1147
 
9.1%
:116
 
7.1%
781
 
5.0%
881
 
5.0%
273
 
4.5%
067
 
4.1%
658
 
3.6%
Other values (3)144
 
8.9%
Latin
ValueCountFrequency (%)
p348
12.0%
s348
12.0%
e348
12.0%
t348
12.0%
o232
8.0%
a232
8.0%
i232
8.0%
m232
8.0%
h116
 
4.0%
d116
 
4.0%
Other values (3)348
12.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII4524
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/464
 
10.3%
p348
 
7.7%
s348
 
7.7%
e348
 
7.7%
t348
 
7.7%
o232
 
5.1%
a232
 
5.1%
i232
 
5.1%
.232
 
5.1%
m232
 
5.1%
Other values (16)1508
33.3%

_embedded.show.id
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct72
Distinct (%)62.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean47710.31034
Minimum1825
Maximum62127
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2022-09-04T23:40:33.959353image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum1825
5-th percentile13047.75
Q149191.25
median52159
Q352780
95-th percentile58056.5
Maximum62127
Range60302
Interquartile range (IQR)3588.75

Descriptive statistics

Standard deviation13308.74493
Coefficient of variation (CV)0.2789490329
Kurtosis5.24347448
Mean47710.31034
Median Absolute Deviation (MAD)1154.5
Skewness-2.420417622
Sum5534396
Variance177122691.6
MonotonicityNot monotonic
2022-09-04T23:40:34.052353image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
527438
 
6.9%
527806
 
5.2%
525216
 
5.2%
519286
 
5.2%
519944
 
3.4%
521103
 
2.6%
524713
 
2.6%
18253
 
2.6%
570303
 
2.6%
525242
 
1.7%
Other values (62)72
62.1%
ValueCountFrequency (%)
18253
2.6%
22661
 
0.9%
25041
 
0.9%
64411
 
0.9%
152502
1.7%
173561
 
0.9%
262681
 
0.9%
283461
 
0.9%
306061
 
0.9%
339441
 
0.9%
ValueCountFrequency (%)
621271
 
0.9%
617551
 
0.9%
586892
1.7%
584261
 
0.9%
583671
 
0.9%
579531
 
0.9%
576891
 
0.9%
574781
 
0.9%
570303
2.6%
568481
 
0.9%

_embedded.show.url
Categorical

HIGH CARDINALITY
HIGH CORRELATION

Distinct72
Distinct (%)62.1%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
https://www.tvmaze.com/shows/52743/the-penalty-zone
 
8
https://www.tvmaze.com/shows/52780/mermaid-prince
 
6
https://www.tvmaze.com/shows/52521/rompan-todo-la-historia-del-rock-en-america-latina
 
6
https://www.tvmaze.com/shows/51928/anitta-made-in-honorio
 
6
https://www.tvmaze.com/shows/51994/the-ripper
 
4
Other values (67)
86 

Length

Max length85
Median length60.5
Mean length52.88793103
Min length41

Characters and Unicode

Total characters6135
Distinct characters39
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique52 ?
Unique (%)44.8%

Sample

1st rowhttps://www.tvmaze.com/shows/49630/kontakty
2nd rowhttps://www.tvmaze.com/shows/52316/mertvye-dusi
3rd rowhttps://www.tvmaze.com/shows/52316/mertvye-dusi
4th rowhttps://www.tvmaze.com/shows/48395/wan-sheng-jie
5th rowhttps://www.tvmaze.com/shows/49206/xian-feng-jian-yu-lu

Common Values

ValueCountFrequency (%)
https://www.tvmaze.com/shows/52743/the-penalty-zone8
 
6.9%
https://www.tvmaze.com/shows/52780/mermaid-prince6
 
5.2%
https://www.tvmaze.com/shows/52521/rompan-todo-la-historia-del-rock-en-america-latina6
 
5.2%
https://www.tvmaze.com/shows/51928/anitta-made-in-honorio6
 
5.2%
https://www.tvmaze.com/shows/51994/the-ripper4
 
3.4%
https://www.tvmaze.com/shows/52110/how-to-ruin-christmas3
 
2.6%
https://www.tvmaze.com/shows/52471/the-expanse-aftershow3
 
2.6%
https://www.tvmaze.com/shows/1825/the-expanse3
 
2.6%
https://www.tvmaze.com/shows/57030/gjor-det-sjol3
 
2.6%
https://www.tvmaze.com/shows/52524/forever-love2
 
1.7%
Other values (62)72
62.1%

Length

2022-09-04T23:40:34.152353image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://www.tvmaze.com/shows/52743/the-penalty-zone8
 
6.9%
https://www.tvmaze.com/shows/52521/rompan-todo-la-historia-del-rock-en-america-latina6
 
5.2%
https://www.tvmaze.com/shows/51928/anitta-made-in-honorio6
 
5.2%
https://www.tvmaze.com/shows/52780/mermaid-prince6
 
5.2%
https://www.tvmaze.com/shows/51994/the-ripper4
 
3.4%
https://www.tvmaze.com/shows/52110/how-to-ruin-christmas3
 
2.6%
https://www.tvmaze.com/shows/52471/the-expanse-aftershow3
 
2.6%
https://www.tvmaze.com/shows/1825/the-expanse3
 
2.6%
https://www.tvmaze.com/shows/57030/gjor-det-sjol3
 
2.6%
https://www.tvmaze.com/shows/52108/psych-hunter2
 
1.7%
Other values (62)72
62.1%

Most occurring characters

ValueCountFrequency (%)
/580
 
9.5%
w492
 
8.0%
t491
 
8.0%
s439
 
7.2%
o375
 
6.1%
e337
 
5.5%
h313
 
5.1%
m308
 
5.0%
a284
 
4.6%
-265
 
4.3%
Other values (29)2251
36.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter4360
71.1%
Other Punctuation928
 
15.1%
Decimal Number582
 
9.5%
Dash Punctuation265
 
4.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
w492
11.3%
t491
11.3%
s439
10.1%
o375
 
8.6%
e337
 
7.7%
h313
 
7.2%
m308
 
7.1%
a284
 
6.5%
p168
 
3.9%
c167
 
3.8%
Other values (15)986
22.6%
Decimal Number
ValueCountFrequency (%)
5113
19.4%
290
15.5%
466
11.3%
163
10.8%
752
8.9%
048
8.2%
841
 
7.0%
641
 
7.0%
336
 
6.2%
932
 
5.5%
Other Punctuation
ValueCountFrequency (%)
/580
62.5%
.232
 
25.0%
:116
 
12.5%
Dash Punctuation
ValueCountFrequency (%)
-265
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin4360
71.1%
Common1775
28.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
w492
11.3%
t491
11.3%
s439
10.1%
o375
 
8.6%
e337
 
7.7%
h313
 
7.2%
m308
 
7.1%
a284
 
6.5%
p168
 
3.9%
c167
 
3.8%
Other values (15)986
22.6%
Common
ValueCountFrequency (%)
/580
32.7%
-265
14.9%
.232
 
13.1%
:116
 
6.5%
5113
 
6.4%
290
 
5.1%
466
 
3.7%
163
 
3.5%
752
 
2.9%
048
 
2.7%
Other values (4)150
 
8.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII6135
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/580
 
9.5%
w492
 
8.0%
t491
 
8.0%
s439
 
7.2%
o375
 
6.1%
e337
 
5.5%
h313
 
5.1%
m308
 
5.0%
a284
 
4.6%
-265
 
4.3%
Other values (29)2251
36.7%

_embedded.show.name
Categorical

HIGH CARDINALITY
HIGH CORRELATION

Distinct72
Distinct (%)62.1%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
The Penalty Zone
 
8
Mermaid Prince
 
6
Rompan todo: La historia del rock en América Latina
 
6
Anitta: Made in Honório
 
6
The Ripper
 
4
Other values (67)
86 

Length

Max length51
Median length26
Mean length18.1637931
Min length6

Characters and Unicode

Total characters2107
Distinct characters94
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique52 ?
Unique (%)44.8%

Sample

1st rowКонтакты
2nd rowМёртвые души
3rd rowМёртвые души
4th rowWan Sheng Jie
5th rowXian Feng Jian Yu Lu

Common Values

ValueCountFrequency (%)
The Penalty Zone8
 
6.9%
Mermaid Prince6
 
5.2%
Rompan todo: La historia del rock en América Latina6
 
5.2%
Anitta: Made in Honório6
 
5.2%
The Ripper4
 
3.4%
How to Ruin Christmas3
 
2.6%
The Expanse Aftershow3
 
2.6%
The Expanse3
 
2.6%
Gjør det sjøl3
 
2.6%
Forever Love2
 
1.7%
Other values (62)72
62.1%

Length

2022-09-04T23:40:34.246352image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
the28
 
7.3%
in8
 
2.1%
penalty8
 
2.1%
zone8
 
2.1%
love7
 
1.8%
la7
 
1.8%
mermaid6
 
1.6%
américa6
 
1.6%
expanse6
 
1.6%
honório6
 
1.6%
Other values (186)291
76.4%

Most occurring characters

ValueCountFrequency (%)
265
 
12.6%
e196
 
9.3%
a136
 
6.5%
i119
 
5.6%
o118
 
5.6%
n117
 
5.6%
r111
 
5.3%
t94
 
4.5%
h66
 
3.1%
s64
 
3.0%
Other values (84)821
39.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1488
70.6%
Uppercase Letter321
 
15.2%
Space Separator265
 
12.6%
Other Punctuation25
 
1.2%
Decimal Number8
 
0.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e196
13.2%
a136
 
9.1%
i119
 
8.0%
o118
 
7.9%
n117
 
7.9%
r111
 
7.5%
t94
 
6.3%
h66
 
4.4%
s64
 
4.3%
l44
 
3.0%
Other values (43)423
28.4%
Uppercase Letter
ValueCountFrequency (%)
T40
 
12.5%
M29
 
9.0%
A24
 
7.5%
L23
 
7.2%
R21
 
6.5%
P21
 
6.5%
S19
 
5.9%
H15
 
4.7%
Y13
 
4.0%
C13
 
4.0%
Other values (21)103
32.1%
Decimal Number
ValueCountFrequency (%)
03
37.5%
22
25.0%
11
 
12.5%
51
 
12.5%
31
 
12.5%
Other Punctuation
ValueCountFrequency (%)
:19
76.0%
'4
 
16.0%
.1
 
4.0%
,1
 
4.0%
Space Separator
ValueCountFrequency (%)
265
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1707
81.0%
Common298
 
14.1%
Cyrillic102
 
4.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
e196
 
11.5%
a136
 
8.0%
i119
 
7.0%
o118
 
6.9%
n117
 
6.9%
r111
 
6.5%
t94
 
5.5%
h66
 
3.9%
s64
 
3.7%
l44
 
2.6%
Other values (42)642
37.6%
Cyrillic
ValueCountFrequency (%)
т9
 
8.8%
р8
 
7.8%
е8
 
7.8%
о7
 
6.9%
а7
 
6.9%
к6
 
5.9%
и6
 
5.9%
у4
 
3.9%
д4
 
3.9%
н4
 
3.9%
Other values (22)39
38.2%
Common
ValueCountFrequency (%)
265
88.9%
:19
 
6.4%
'4
 
1.3%
03
 
1.0%
22
 
0.7%
11
 
0.3%
.1
 
0.3%
51
 
0.3%
,1
 
0.3%
31
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII1984
94.2%
Cyrillic102
 
4.8%
None21
 
1.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
265
 
13.4%
e196
 
9.9%
a136
 
6.9%
i119
 
6.0%
o118
 
5.9%
n117
 
5.9%
r111
 
5.6%
t94
 
4.7%
h66
 
3.3%
s64
 
3.2%
Other values (49)698
35.2%
Cyrillic
ValueCountFrequency (%)
т9
 
8.8%
р8
 
7.8%
е8
 
7.8%
о7
 
6.9%
а7
 
6.9%
к6
 
5.9%
и6
 
5.9%
у4
 
3.9%
д4
 
3.9%
н4
 
3.9%
Other values (22)39
38.2%
None
ValueCountFrequency (%)
ø9
42.9%
é6
28.6%
ó6
28.6%

_embedded.show.type
Categorical

HIGH CORRELATION

Distinct9
Distinct (%)7.8%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
Scripted
53 
Documentary
21 
Talk Show
13 
Reality
10 
Animation
Other values (4)
10 

Length

Max length11
Median length9
Mean length8.534482759
Min length4

Characters and Unicode

Total characters990
Distinct characters27
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowGame Show
2nd rowScripted
3rd rowScripted
4th rowAnimation
5th rowAnimation

Common Values

ValueCountFrequency (%)
Scripted53
45.7%
Documentary21
 
18.1%
Talk Show13
 
11.2%
Reality10
 
8.6%
Animation9
 
7.8%
Game Show3
 
2.6%
Sports3
 
2.6%
News2
 
1.7%
Variety2
 
1.7%

Length

2022-09-04T23:40:34.335352image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-04T23:40:34.429350image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
scripted53
40.2%
documentary21
 
15.9%
show16
 
12.1%
talk13
 
9.8%
reality10
 
7.6%
animation9
 
6.8%
game3
 
2.3%
sports3
 
2.3%
news2
 
1.5%
variety2
 
1.5%

Most occurring characters

ValueCountFrequency (%)
t98
 
9.9%
e91
 
9.2%
i83
 
8.4%
r79
 
8.0%
c74
 
7.5%
S72
 
7.3%
a58
 
5.9%
p56
 
5.7%
d53
 
5.4%
o49
 
4.9%
Other values (17)277
28.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter842
85.1%
Uppercase Letter132
 
13.3%
Space Separator16
 
1.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t98
11.6%
e91
10.8%
i83
9.9%
r79
9.4%
c74
8.8%
a58
 
6.9%
p56
 
6.7%
d53
 
6.3%
o49
 
5.8%
n39
 
4.6%
Other values (8)162
19.2%
Uppercase Letter
ValueCountFrequency (%)
S72
54.5%
D21
 
15.9%
T13
 
9.8%
R10
 
7.6%
A9
 
6.8%
G3
 
2.3%
N2
 
1.5%
V2
 
1.5%
Space Separator
ValueCountFrequency (%)
16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin974
98.4%
Common16
 
1.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
t98
 
10.1%
e91
 
9.3%
i83
 
8.5%
r79
 
8.1%
c74
 
7.6%
S72
 
7.4%
a58
 
6.0%
p56
 
5.7%
d53
 
5.4%
o49
 
5.0%
Other values (16)261
26.8%
Common
ValueCountFrequency (%)
16
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII990
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t98
 
9.9%
e91
 
9.2%
i83
 
8.4%
r79
 
8.0%
c74
 
7.5%
S72
 
7.3%
a58
 
5.9%
p56
 
5.7%
d53
 
5.4%
o49
 
4.9%
Other values (17)277
28.0%

_embedded.show.language
Categorical

HIGH CORRELATION
MISSING

Distinct15
Distinct (%)13.6%
Missing6
Missing (%)5.2%
Memory size1.0 KiB
Chinese
39 
English
29 
Norwegian
Russian
Spanish
Other values (10)
20 

Length

Max length10
Median length7
Mean length7.263636364
Min length4

Characters and Unicode

Total characters799
Distinct characters32
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)4.5%

Sample

1st rowRussian
2nd rowRussian
3rd rowRussian
4th rowChinese
5th rowChinese

Common Values

ValueCountFrequency (%)
Chinese39
33.6%
English29
25.0%
Norwegian8
 
6.9%
Russian7
 
6.0%
Spanish7
 
6.0%
Portuguese7
 
6.0%
Korean2
 
1.7%
Arabic2
 
1.7%
Japanese2
 
1.7%
Thai2
 
1.7%
Other values (5)5
 
4.3%
(Missing)6
 
5.2%

Length

2022-09-04T23:40:34.523350image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
chinese39
35.5%
english29
26.4%
norwegian8
 
7.3%
russian7
 
6.4%
spanish7
 
6.4%
portuguese7
 
6.4%
korean2
 
1.8%
arabic2
 
1.8%
japanese2
 
1.8%
thai2
 
1.8%
Other values (5)5
 
4.5%

Most occurring characters

ValueCountFrequency (%)
e107
13.4%
n99
12.4%
s98
12.3%
i97
12.1%
h80
10.0%
g45
 
5.6%
C39
 
4.9%
a38
 
4.8%
E29
 
3.6%
l29
 
3.6%
Other values (22)138
17.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter689
86.2%
Uppercase Letter110
 
13.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e107
15.5%
n99
14.4%
s98
14.2%
i97
14.1%
h80
11.6%
g45
6.5%
a38
 
5.5%
l29
 
4.2%
u23
 
3.3%
r22
 
3.2%
Other values (8)51
7.4%
Uppercase Letter
ValueCountFrequency (%)
C39
35.5%
E29
26.4%
N8
 
7.3%
P7
 
6.4%
S7
 
6.4%
R7
 
6.4%
K3
 
2.7%
A2
 
1.8%
J2
 
1.8%
T2
 
1.8%
Other values (4)4
 
3.6%

Most occurring scripts

ValueCountFrequency (%)
Latin799
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e107
13.4%
n99
12.4%
s98
12.3%
i97
12.1%
h80
10.0%
g45
 
5.6%
C39
 
4.9%
a38
 
4.8%
E29
 
3.6%
l29
 
3.6%
Other values (22)138
17.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII799
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e107
13.4%
n99
12.4%
s98
12.3%
i97
12.1%
h80
10.0%
g45
 
5.6%
C39
 
4.9%
a38
 
4.8%
E29
 
3.6%
l29
 
3.6%
Other values (22)138
17.3%

_embedded.show.genres
Unsupported

REJECTED
UNSUPPORTED

Missing0
Missing (%)0.0%
Memory size1.0 KiB

_embedded.show.status
Categorical

HIGH CORRELATION

Distinct3
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
Ended
65 
Running
45 
To Be Determined
 
6

Length

Max length16
Median length5
Mean length6.344827586
Min length5

Characters and Unicode

Total characters736
Distinct characters16
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowRunning
2nd rowEnded
3rd rowEnded
4th rowRunning
5th rowRunning

Common Values

ValueCountFrequency (%)
Ended65
56.0%
Running45
38.8%
To Be Determined6
 
5.2%

Length

2022-09-04T23:40:34.601573image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-04T23:40:34.674573image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
ended65
50.8%
running45
35.2%
to6
 
4.7%
be6
 
4.7%
determined6
 
4.7%

Most occurring characters

ValueCountFrequency (%)
n206
28.0%
d136
18.5%
e89
12.1%
E65
 
8.8%
i51
 
6.9%
R45
 
6.1%
u45
 
6.1%
g45
 
6.1%
12
 
1.6%
T6
 
0.8%
Other values (6)36
 
4.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter596
81.0%
Uppercase Letter128
 
17.4%
Space Separator12
 
1.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n206
34.6%
d136
22.8%
e89
14.9%
i51
 
8.6%
u45
 
7.6%
g45
 
7.6%
o6
 
1.0%
t6
 
1.0%
r6
 
1.0%
m6
 
1.0%
Uppercase Letter
ValueCountFrequency (%)
E65
50.8%
R45
35.2%
T6
 
4.7%
B6
 
4.7%
D6
 
4.7%
Space Separator
ValueCountFrequency (%)
12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin724
98.4%
Common12
 
1.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
n206
28.5%
d136
18.8%
e89
12.3%
E65
 
9.0%
i51
 
7.0%
R45
 
6.2%
u45
 
6.2%
g45
 
6.2%
T6
 
0.8%
o6
 
0.8%
Other values (5)30
 
4.1%
Common
ValueCountFrequency (%)
12
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII736
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n206
28.0%
d136
18.5%
e89
12.1%
E65
 
8.8%
i51
 
6.9%
R45
 
6.1%
u45
 
6.1%
g45
 
6.1%
12
 
1.6%
T6
 
0.8%
Other values (6)36
 
4.9%

_embedded.show.runtime
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct20
Distinct (%)28.6%
Missing46
Missing (%)39.7%
Infinite0
Infinite (%)0.0%
Mean40.95714286
Minimum2
Maximum120
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2022-09-04T23:40:34.739573image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile5.9
Q123.5
median45
Q345
95-th percentile106.5
Maximum120
Range118
Interquartile range (IQR)21.5

Descriptive statistics

Standard deviation26.38424855
Coefficient of variation (CV)0.6441916283
Kurtosis2.860472733
Mean40.95714286
Median Absolute Deviation (MAD)13.5
Skewness1.419375647
Sum2867
Variance696.1285714
MonotonicityNot monotonic
2022-09-04T23:40:34.821279image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
4531
26.7%
305
 
4.3%
205
 
4.3%
1204
 
3.4%
73
 
2.6%
603
 
2.6%
253
 
2.6%
52
 
1.7%
432
 
1.7%
902
 
1.7%
Other values (10)10
 
8.6%
(Missing)46
39.7%
ValueCountFrequency (%)
21
 
0.9%
41
 
0.9%
52
 
1.7%
73
2.6%
81
 
0.9%
121
 
0.9%
161
 
0.9%
181
 
0.9%
191
 
0.9%
205
4.3%
ValueCountFrequency (%)
1204
 
3.4%
902
 
1.7%
603
 
2.6%
551
 
0.9%
4531
26.7%
432
 
1.7%
331
 
0.9%
305
 
4.3%
253
 
2.6%
231
 
0.9%

_embedded.show.averageRuntime
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct33
Distinct (%)30.0%
Missing6
Missing (%)5.2%
Infinite0
Infinite (%)0.0%
Mean38.18181818
Minimum2
Maximum120
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2022-09-04T23:40:34.901023image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile5
Q120.75
median45
Q345
95-th percentile70.7
Maximum120
Range118
Interquartile range (IQR)24.25

Descriptive statistics

Standard deviation23.2703228
Coefficient of variation (CV)0.6094608353
Kurtosis3.237155019
Mean38.18181818
Median Absolute Deviation (MAD)13.5
Skewness1.238431596
Sum4200
Variance541.5079233
MonotonicityNot monotonic
2022-09-04T23:40:34.988024image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
4530
25.9%
3010
 
8.6%
509
 
7.8%
55
 
4.3%
205
 
4.3%
255
 
4.3%
74
 
3.4%
494
 
3.4%
123
 
2.6%
323
 
2.6%
Other values (23)32
27.6%
(Missing)6
 
5.2%
ValueCountFrequency (%)
21
 
0.9%
41
 
0.9%
55
4.3%
74
3.4%
81
 
0.9%
91
 
0.9%
112
 
1.7%
123
2.6%
141
 
0.9%
151
 
0.9%
ValueCountFrequency (%)
1203
 
2.6%
1101
 
0.9%
901
 
0.9%
771
 
0.9%
631
 
0.9%
603
 
2.6%
591
 
0.9%
553
 
2.6%
509
7.8%
494
3.4%

_embedded.show.premiered
Categorical

HIGH CARDINALITY
HIGH CORRELATION

Distinct58
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
2020-12-16
32 
2020-11-25
 
6
2020-11-23
 
4
2020-12-14
 
4
2020-12-09
 
3
Other values (53)
67 

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters1160
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique43 ?
Unique (%)37.1%

Sample

1st row2019-04-03
2nd row2020-12-09
3rd row2020-12-09
4th row2020-04-01
5th row2020-07-11

Common Values

ValueCountFrequency (%)
2020-12-1632
27.6%
2020-11-256
 
5.2%
2020-11-234
 
3.4%
2020-12-144
 
3.4%
2020-12-093
 
2.6%
2020-12-083
 
2.6%
2020-11-183
 
2.6%
2015-12-143
 
2.6%
2020-07-083
 
2.6%
2013-12-242
 
1.7%
Other values (48)53
45.7%

Length

2022-09-04T23:40:35.070024image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2020-12-1632
27.6%
2020-11-256
 
5.2%
2020-11-234
 
3.4%
2020-12-144
 
3.4%
2020-12-093
 
2.6%
2020-12-083
 
2.6%
2020-11-183
 
2.6%
2015-12-143
 
2.6%
2020-07-083
 
2.6%
2020-12-022
 
1.7%
Other values (48)53
45.7%

Most occurring characters

ValueCountFrequency (%)
2288
24.8%
0264
22.8%
-232
20.0%
1215
18.5%
639
 
3.4%
929
 
2.5%
423
 
2.0%
823
 
2.0%
320
 
1.7%
518
 
1.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number928
80.0%
Dash Punctuation232
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2288
31.0%
0264
28.4%
1215
23.2%
639
 
4.2%
929
 
3.1%
423
 
2.5%
823
 
2.5%
320
 
2.2%
518
 
1.9%
79
 
1.0%
Dash Punctuation
ValueCountFrequency (%)
-232
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common1160
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2288
24.8%
0264
22.8%
-232
20.0%
1215
18.5%
639
 
3.4%
929
 
2.5%
423
 
2.0%
823
 
2.0%
320
 
1.7%
518
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII1160
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2288
24.8%
0264
22.8%
-232
20.0%
1215
18.5%
639
 
3.4%
929
 
2.5%
423
 
2.0%
823
 
2.0%
320
 
1.7%
518
 
1.6%

_embedded.show.ended
Categorical

HIGH CORRELATION
MISSING

Distinct17
Distinct (%)26.2%
Missing51
Missing (%)44.0%
Memory size1.0 KiB
2020-12-16
27 
2021-01-09
2020-12-30
2020-12-22
2021-01-05
Other values (12)
17 

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters650
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)12.3%

Sample

1st row2020-12-16
2nd row2020-12-16
3rd row2021-01-06
4th row2020-12-16
5th row2021-01-27

Common Values

ValueCountFrequency (%)
2020-12-1627
23.3%
2021-01-098
 
6.9%
2020-12-305
 
4.3%
2020-12-224
 
3.4%
2021-01-054
 
3.4%
2022-01-143
 
2.6%
2021-01-272
 
1.7%
2021-01-142
 
1.7%
2020-12-232
 
1.7%
2020-12-281
 
0.9%
Other values (7)7
 
6.0%
(Missing)51
44.0%

Length

2022-09-04T23:40:35.145093image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2020-12-1627
41.5%
2021-01-098
 
12.3%
2020-12-305
 
7.7%
2020-12-224
 
6.2%
2021-01-054
 
6.2%
2022-01-143
 
4.6%
2021-01-142
 
3.1%
2020-12-232
 
3.1%
2021-01-272
 
3.1%
2020-12-281
 
1.5%
Other values (7)7
 
10.8%

Most occurring characters

ValueCountFrequency (%)
2191
29.4%
0150
23.1%
-130
20.0%
1117
18.0%
628
 
4.3%
311
 
1.7%
98
 
1.2%
46
 
0.9%
54
 
0.6%
83
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number520
80.0%
Dash Punctuation130
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2191
36.7%
0150
28.8%
1117
22.5%
628
 
5.4%
311
 
2.1%
98
 
1.5%
46
 
1.2%
54
 
0.8%
83
 
0.6%
72
 
0.4%
Dash Punctuation
ValueCountFrequency (%)
-130
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common650
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2191
29.4%
0150
23.1%
-130
20.0%
1117
18.0%
628
 
4.3%
311
 
1.7%
98
 
1.2%
46
 
0.9%
54
 
0.6%
83
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII650
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2191
29.4%
0150
23.1%
-130
20.0%
1117
18.0%
628
 
4.3%
311
 
1.7%
98
 
1.2%
46
 
0.9%
54
 
0.6%
83
 
0.5%

_embedded.show.officialSite
Categorical

HIGH CARDINALITY
HIGH CORRELATION
MISSING

Distinct63
Distinct (%)63.0%
Missing16
Missing (%)13.8%
Memory size1.0 KiB
https://www.iqiyi.com/a_19rrhllpip.html
https://www.netflix.com/title/81302719
 
6
https://www.netflix.com/title/81006953
 
6
https://www.netflix.com/title/81006684
 
4
https://tv.nrk.no/serie/gjoer-det-sjoel
 
3
Other values (58)
73 

Length

Max length250
Median length86
Mean length50.35
Min length18

Characters and Unicode

Total characters5035
Distinct characters74
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique46 ?
Unique (%)46.0%

Sample

1st rowhttps://www.youtube.com/playlist?list=PLZ1FUdedsrSJubWkFFh5vKHzawzQk1mYI
2nd rowhttps://www.ivi.ru/watch/mertvyie-dushi-2020
3rd rowhttps://www.ivi.ru/watch/mertvyie-dushi-2020
4th rowhttps://v.qq.com/detail/a/awnia0n2erqryf3.html
5th rowhttps://v.qq.com/detail/m/mzc00200hc38s5x.html

Common Values

ValueCountFrequency (%)
https://www.iqiyi.com/a_19rrhllpip.html8
 
6.9%
https://www.netflix.com/title/813027196
 
5.2%
https://www.netflix.com/title/810069536
 
5.2%
https://www.netflix.com/title/810066844
 
3.4%
https://tv.nrk.no/serie/gjoer-det-sjoel3
 
2.6%
https://www.netflix.com/title/812944173
 
2.6%
https://www.youtube.com/playlist?list=PLWz2DO39R-NU5FW-aFfilRvyeg9oXMTgp3
 
2.6%
https://www.amazon.com/dp/B07YL9WK1S/3
 
2.6%
https://v.qq.com/detail/m/mzc00200dnvb1wh.html2
 
1.7%
https://v.qq.com/detail/m/mzc00200tu76tos.html2
 
1.7%
Other values (53)60
51.7%
(Missing)16
 
13.8%

Length

2022-09-04T23:40:35.221024image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://www.iqiyi.com/a_19rrhllpip.html8
 
8.0%
https://www.netflix.com/title/810069536
 
6.0%
https://www.netflix.com/title/813027196
 
6.0%
https://www.netflix.com/title/810066844
 
4.0%
https://tv.nrk.no/serie/gjoer-det-sjoel3
 
3.0%
https://www.netflix.com/title/812944173
 
3.0%
https://www.youtube.com/playlist?list=plwz2do39r-nu5fw-affilrvyeg9oxmtgp3
 
3.0%
https://www.amazon.com/dp/b07yl9wk1s3
 
3.0%
https://v.youku.com/v_show/id_xndk4otuxmzg1mg==.html?spm=a2hbt.13141534.0.13141534&s=6eefbfbd4befbfbd32ef2
 
2.0%
https://v.qq.com/detail/m/mzc00200ur8p8zp.html2
 
2.0%
Other values (53)60
60.0%

Most occurring characters

ValueCountFrequency (%)
/404
 
8.0%
t400
 
7.9%
w221
 
4.4%
.220
 
4.4%
s212
 
4.2%
e203
 
4.0%
h188
 
3.7%
o188
 
3.7%
i180
 
3.6%
l166
 
3.3%
Other values (64)2653
52.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter3095
61.5%
Other Punctuation882
 
17.5%
Decimal Number613
 
12.2%
Uppercase Letter340
 
6.8%
Dash Punctuation50
 
1.0%
Math Symbol31
 
0.6%
Connector Punctuation24
 
0.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t400
 
12.9%
w221
 
7.1%
s212
 
6.8%
e203
 
6.6%
h188
 
6.1%
o188
 
6.1%
i180
 
5.8%
l166
 
5.4%
m164
 
5.3%
p164
 
5.3%
Other values (16)1009
32.6%
Uppercase Letter
ValueCountFrequency (%)
B51
15.0%
E49
 
14.4%
A21
 
6.2%
W15
 
4.4%
L14
 
4.1%
U13
 
3.8%
F13
 
3.8%
S13
 
3.8%
Y13
 
3.8%
D13
 
3.8%
Other values (16)125
36.8%
Decimal Number
ValueCountFrequency (%)
0110
17.9%
188
14.4%
886
14.0%
979
12.9%
248
7.8%
544
 
7.2%
444
 
7.2%
341
 
6.7%
637
 
6.0%
736
 
5.9%
Other Punctuation
ValueCountFrequency (%)
/404
45.8%
.220
24.9%
%131
 
14.9%
:100
 
11.3%
?16
 
1.8%
&9
 
1.0%
#1
 
0.1%
!1
 
0.1%
Math Symbol
ValueCountFrequency (%)
=29
93.5%
+2
 
6.5%
Dash Punctuation
ValueCountFrequency (%)
-50
100.0%
Connector Punctuation
ValueCountFrequency (%)
_24
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin3435
68.2%
Common1600
31.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
t400
 
11.6%
w221
 
6.4%
s212
 
6.2%
e203
 
5.9%
h188
 
5.5%
o188
 
5.5%
i180
 
5.2%
l166
 
4.8%
m164
 
4.8%
p164
 
4.8%
Other values (42)1349
39.3%
Common
ValueCountFrequency (%)
/404
25.2%
.220
13.8%
%131
 
8.2%
0110
 
6.9%
:100
 
6.2%
188
 
5.5%
886
 
5.4%
979
 
4.9%
-50
 
3.1%
248
 
3.0%
Other values (12)284
17.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII5035
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/404
 
8.0%
t400
 
7.9%
w221
 
4.4%
.220
 
4.4%
s212
 
4.2%
e203
 
4.0%
h188
 
3.7%
o188
 
3.7%
i180
 
3.6%
l166
 
3.3%
Other values (64)2653
52.7%

_embedded.show.schedule.time
Categorical

HIGH CORRELATION

Distinct10
Distinct (%)8.6%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
82 
20:00
15 
21:00
 
7
10:00
 
4
00:00
 
2
Other values (5)
 
6

Length

Max length5
Median length0
Mean length1.465517241
Min length0

Characters and Unicode

Total characters170
Distinct characters10
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)3.4%

Sample

1st row
2nd row
3rd row
4th row10:00
5th row10:00

Common Values

ValueCountFrequency (%)
82
70.7%
20:0015
 
12.9%
21:007
 
6.0%
10:004
 
3.4%
00:002
 
1.7%
19:002
 
1.7%
12:001
 
0.9%
06:001
 
0.9%
17:351
 
0.9%
08:301
 
0.9%

Length

2022-09-04T23:40:35.302100image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-04T23:40:35.378383image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
20:0015
44.1%
21:007
20.6%
10:004
 
11.8%
00:002
 
5.9%
19:002
 
5.9%
12:001
 
2.9%
06:001
 
2.9%
17:351
 
2.9%
08:301
 
2.9%

Most occurring characters

ValueCountFrequency (%)
090
52.9%
:34
 
20.0%
223
 
13.5%
115
 
8.8%
92
 
1.2%
32
 
1.2%
61
 
0.6%
71
 
0.6%
51
 
0.6%
81
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number136
80.0%
Other Punctuation34
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
090
66.2%
223
 
16.9%
115
 
11.0%
92
 
1.5%
32
 
1.5%
61
 
0.7%
71
 
0.7%
51
 
0.7%
81
 
0.7%
Other Punctuation
ValueCountFrequency (%)
:34
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common170
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
090
52.9%
:34
 
20.0%
223
 
13.5%
115
 
8.8%
92
 
1.2%
32
 
1.2%
61
 
0.6%
71
 
0.6%
51
 
0.6%
81
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII170
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
090
52.9%
:34
 
20.0%
223
 
13.5%
115
 
8.8%
92
 
1.2%
32
 
1.2%
61
 
0.6%
71
 
0.6%
51
 
0.6%
81
 
0.6%

_embedded.show.schedule.days
Unsupported

REJECTED
UNSUPPORTED

Missing0
Missing (%)0.0%
Memory size1.0 KiB

_embedded.show.rating.average
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct4
Distinct (%)40.0%
Missing106
Missing (%)91.4%
Memory size1.0 KiB
8.1
8.8
7.2
7.3

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters30
Distinct characters6
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)10.0%

Sample

1st row7.3
2nd row8.8
3rd row8.8
4th row8.8
5th row7.2

Common Values

ValueCountFrequency (%)
8.14
 
3.4%
8.83
 
2.6%
7.22
 
1.7%
7.31
 
0.9%
(Missing)106
91.4%

Length

2022-09-04T23:40:35.454390image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-04T23:40:35.518385image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
8.14
40.0%
8.83
30.0%
7.22
20.0%
7.31
 
10.0%

Most occurring characters

ValueCountFrequency (%)
810
33.3%
.10
33.3%
14
 
13.3%
73
 
10.0%
22
 
6.7%
31
 
3.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number20
66.7%
Other Punctuation10
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
810
50.0%
14
 
20.0%
73
 
15.0%
22
 
10.0%
31
 
5.0%
Other Punctuation
ValueCountFrequency (%)
.10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common30
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
810
33.3%
.10
33.3%
14
 
13.3%
73
 
10.0%
22
 
6.7%
31
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII30
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
810
33.3%
.10
33.3%
14
 
13.3%
73
 
10.0%
22
 
6.7%
31
 
3.3%

_embedded.show.weight
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct43
Distinct (%)37.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean31.40517241
Minimum3
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2022-09-04T23:40:35.591385image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile6.75
Q120
median23
Q335
95-th percentile85
Maximum100
Range97
Interquartile range (IQR)15

Descriptive statistics

Standard deviation23.86810805
Coefficient of variation (CV)0.7600056364
Kurtosis1.301802925
Mean31.40517241
Median Absolute Deviation (MAD)8
Skewness1.442827452
Sum3643
Variance569.6865817
MonotonicityNot monotonic
2022-09-04T23:40:35.680384image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
2018
 
15.5%
238
 
6.9%
266
 
5.2%
225
 
4.3%
274
 
3.4%
804
 
3.4%
44
 
3.4%
474
 
3.4%
84
 
3.4%
243
 
2.6%
Other values (33)56
48.3%
ValueCountFrequency (%)
31
 
0.9%
44
3.4%
61
 
0.9%
73
2.6%
84
3.4%
92
1.7%
101
 
0.9%
122
1.7%
132
1.7%
142
1.7%
ValueCountFrequency (%)
1003
2.6%
961
 
0.9%
901
 
0.9%
881
 
0.9%
841
 
0.9%
804
3.4%
741
 
0.9%
683
2.6%
611
 
0.9%
602
1.7%

_embedded.show.network
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing116
Missing (%)100.0%
Memory size1.0 KiB

_embedded.show.webChannel.id
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct27
Distinct (%)23.9%
Missing3
Missing (%)2.6%
Infinite0
Infinite (%)0.0%
Mean98.01769912
Minimum1
Maximum516
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2022-09-04T23:40:35.878383image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q121
median67
Q3104
95-th percentile337
Maximum516
Range515
Interquartile range (IQR)83

Descriptive statistics

Standard deviation116.9934356
Coefficient of variation (CV)1.193595
Kurtosis2.403510081
Mean98.01769912
Median Absolute Deviation (MAD)46
Skewness1.675537239
Sum11076
Variance13687.46397
MonotonicityNot monotonic
2022-09-04T23:40:35.956385image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
2122
19.0%
120
17.2%
10419
16.4%
6710
8.6%
1185
 
4.3%
2384
 
3.4%
3273
 
2.6%
33
 
2.6%
303
 
2.6%
2262
 
1.7%
Other values (17)22
19.0%
(Missing)3
 
2.6%
ValueCountFrequency (%)
120
17.2%
33
 
2.6%
152
 
1.7%
201
 
0.9%
2122
19.0%
303
 
2.6%
512
 
1.7%
6710
8.6%
882
 
1.7%
991
 
0.9%
ValueCountFrequency (%)
5161
 
0.9%
4981
 
0.9%
4521
 
0.9%
3792
1.7%
3372
1.7%
3273
2.6%
3211
 
0.9%
3111
 
0.9%
2384
3.4%
2262
1.7%

_embedded.show.webChannel.name
Categorical

HIGH CORRELATION
MISSING

Distinct27
Distinct (%)23.9%
Missing3
Missing (%)2.6%
Memory size1.0 KiB
YouTube
22 
Netflix
20 
Tencent QQ
19 
iQIYI
10 
Youku
Other values (22)
37 

Length

Max length17
Median length14
Mean length7.796460177
Min length3

Characters and Unicode

Total characters881
Distinct characters49
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12 ?
Unique (%)10.6%

Sample

1st rowYouTube
2nd rowivi
3rd rowivi
4th rowTencent QQ
5th rowTencent QQ

Common Values

ValueCountFrequency (%)
YouTube22
19.0%
Netflix20
17.2%
Tencent QQ19
16.4%
iQIYI10
8.6%
Youku5
 
4.3%
NRK TV4
 
3.4%
TV 2 Play3
 
2.6%
Prime Video3
 
2.6%
Naver TVCast3
 
2.6%
Mango TV2
 
1.7%
Other values (17)22
19.0%
(Missing)3
 
2.6%

Length

2022-09-04T23:40:36.038394image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
youtube22
14.0%
netflix20
12.7%
tencent19
12.1%
qq19
12.1%
tv11
 
7.0%
iqiyi10
 
6.4%
youku5
 
3.2%
nrk4
 
2.5%
play3
 
1.9%
prime3
 
1.9%
Other values (26)41
26.1%

Most occurring characters

ValueCountFrequency (%)
e101
 
11.5%
u60
 
6.8%
T56
 
6.4%
i54
 
6.1%
t51
 
5.8%
Q48
 
5.4%
o45
 
5.1%
44
 
5.0%
n42
 
4.8%
Y37
 
4.2%
Other values (39)343
38.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter572
64.9%
Uppercase Letter260
29.5%
Space Separator44
 
5.0%
Decimal Number3
 
0.3%
Math Symbol1
 
0.1%
Other Punctuation1
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e101
17.7%
u60
10.5%
i54
9.4%
t51
8.9%
o45
 
7.9%
n42
 
7.3%
l34
 
5.9%
b28
 
4.9%
c23
 
4.0%
x20
 
3.5%
Other values (14)114
19.9%
Uppercase Letter
ValueCountFrequency (%)
T56
21.5%
Q48
18.5%
Y37
14.2%
N31
11.9%
I22
 
8.5%
V19
 
7.3%
W8
 
3.1%
P8
 
3.1%
R5
 
1.9%
C4
 
1.5%
Other values (11)22
 
8.5%
Space Separator
ValueCountFrequency (%)
44
100.0%
Decimal Number
ValueCountFrequency (%)
23
100.0%
Math Symbol
ValueCountFrequency (%)
+1
100.0%
Other Punctuation
ValueCountFrequency (%)
.1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin832
94.4%
Common49
 
5.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
e101
 
12.1%
u60
 
7.2%
T56
 
6.7%
i54
 
6.5%
t51
 
6.1%
Q48
 
5.8%
o45
 
5.4%
n42
 
5.0%
Y37
 
4.4%
l34
 
4.1%
Other values (35)304
36.5%
Common
ValueCountFrequency (%)
44
89.8%
23
 
6.1%
+1
 
2.0%
.1
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII881
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e101
 
11.5%
u60
 
6.8%
T56
 
6.4%
i54
 
6.1%
t51
 
5.8%
Q48
 
5.4%
o45
 
5.1%
44
 
5.0%
n42
 
4.8%
Y37
 
4.2%
Other values (39)343
38.9%

_embedded.show.webChannel.country
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing116
Missing (%)100.0%
Memory size1.0 KiB

_embedded.show.webChannel.officialSite
Categorical

HIGH CORRELATION
MISSING

Distinct11
Distinct (%)12.9%
Missing31
Missing (%)26.7%
Memory size1.0 KiB
https://www.youtube.com
22 
https://www.netflix.com/
20 
https://v.qq.com/
19 
https://www.iq.com/
10 
https://tv.naver.com/
Other values (6)
11 

Length

Max length30
Median length24
Mean length21.41176471
Min length17

Characters and Unicode

Total characters1820
Distinct characters26
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)2.4%

Sample

1st rowhttps://www.youtube.com
2nd rowhttps://www.ivi.ru/
3rd rowhttps://www.ivi.ru/
4th rowhttps://v.qq.com/
5th rowhttps://v.qq.com/

Common Values

ValueCountFrequency (%)
https://www.youtube.com22
19.0%
https://www.netflix.com/20
17.2%
https://v.qq.com/19
16.4%
https://www.iq.com/10
 
8.6%
https://tv.naver.com/3
 
2.6%
https://www.primevideo.com3
 
2.6%
https://www.ivi.ru/2
 
1.7%
https://w.mgtv.com/2
 
1.7%
https://www.linetv.tw/2
 
1.7%
http://www.wowpresentsplus.com1
 
0.9%
(Missing)31
26.7%

Length

2022-09-04T23:40:36.118638image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://www.youtube.com22
25.9%
https://www.netflix.com20
23.5%
https://v.qq.com19
22.4%
https://www.iq.com10
11.8%
https://tv.naver.com3
 
3.5%
https://www.primevideo.com3
 
3.5%
https://www.ivi.ru2
 
2.4%
https://w.mgtv.com2
 
2.4%
https://www.linetv.tw2
 
2.4%
http://www.wowpresentsplus.com1
 
1.2%

Most occurring characters

ValueCountFrequency (%)
/229
12.6%
t222
12.2%
w189
10.4%
.170
 
9.3%
o108
 
5.9%
p91
 
5.0%
s89
 
4.9%
m86
 
4.7%
h85
 
4.7%
:85
 
4.7%
Other values (16)466
25.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1336
73.4%
Other Punctuation484
 
26.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t222
16.6%
w189
14.1%
o108
 
8.1%
p91
 
6.8%
s89
 
6.7%
m86
 
6.4%
h85
 
6.4%
c82
 
6.1%
e56
 
4.2%
u48
 
3.6%
Other values (13)280
21.0%
Other Punctuation
ValueCountFrequency (%)
/229
47.3%
.170
35.1%
:85
 
17.6%

Most occurring scripts

ValueCountFrequency (%)
Latin1336
73.4%
Common484
 
26.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
t222
16.6%
w189
14.1%
o108
 
8.1%
p91
 
6.8%
s89
 
6.7%
m86
 
6.4%
h85
 
6.4%
c82
 
6.1%
e56
 
4.2%
u48
 
3.6%
Other values (13)280
21.0%
Common
ValueCountFrequency (%)
/229
47.3%
.170
35.1%
:85
 
17.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII1820
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/229
12.6%
t222
12.2%
w189
10.4%
.170
 
9.3%
o108
 
5.9%
p91
 
5.0%
s89
 
4.9%
m86
 
4.7%
h85
 
4.7%
:85
 
4.7%
Other values (16)466
25.6%

_embedded.show.dvdCountry
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing116
Missing (%)100.0%
Memory size1.0 KiB

_embedded.show.externals.tvrage
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct3
Distinct (%)60.0%
Missing111
Missing (%)95.7%
Memory size1.0 KiB
41967.0
19056.0
25100.0

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters35
Distinct characters9
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)40.0%

Sample

1st row41967.0
2nd row41967.0
3rd row41967.0
4th row19056.0
5th row25100.0

Common Values

ValueCountFrequency (%)
41967.03
 
2.6%
19056.01
 
0.9%
25100.01
 
0.9%
(Missing)111
95.7%

Length

2022-09-04T23:40:36.192631image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-04T23:40:36.262631image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
41967.03
60.0%
19056.01
 
20.0%
25100.01
 
20.0%

Most occurring characters

ValueCountFrequency (%)
08
22.9%
15
14.3%
.5
14.3%
94
11.4%
64
11.4%
43
 
8.6%
73
 
8.6%
52
 
5.7%
21
 
2.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number30
85.7%
Other Punctuation5
 
14.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
08
26.7%
15
16.7%
94
13.3%
64
13.3%
43
 
10.0%
73
 
10.0%
52
 
6.7%
21
 
3.3%
Other Punctuation
ValueCountFrequency (%)
.5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common35
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
08
22.9%
15
14.3%
.5
14.3%
94
11.4%
64
11.4%
43
 
8.6%
73
 
8.6%
52
 
5.7%
21
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII35
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
08
22.9%
15
14.3%
.5
14.3%
94
11.4%
64
11.4%
43
 
8.6%
73
 
8.6%
52
 
5.7%
21
 
2.9%

_embedded.show.externals.thetvdb
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct49
Distinct (%)66.2%
Missing42
Missing (%)36.2%
Infinite0
Infinite (%)0.0%
Mean363580.3378
Minimum104271
Maximum410086
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2022-09-04T23:40:36.343630image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum104271
5-th percentile277176.7
Q1357399.5
median391453
Q3392343.25
95-th percentile395939.2
Maximum410086
Range305815
Interquartile range (IQR)34943.75

Descriptive statistics

Standard deviation55371.69677
Coefficient of variation (CV)0.1522956304
Kurtosis8.438847513
Mean363580.3378
Median Absolute Deviation (MAD)2973.5
Skewness-2.662559084
Sum26904945
Variance3066024803
MonotonicityNot monotonic
2022-09-04T23:40:36.437559image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=49)
ValueCountFrequency (%)
3921626
 
5.2%
3914536
 
5.2%
3920964
 
3.4%
3922873
 
2.6%
2806193
 
2.6%
3930602
 
1.7%
3926792
 
1.7%
3933812
 
1.7%
2787932
 
1.7%
3923622
 
1.7%
Other values (39)42
36.2%
(Missing)42
36.2%
ValueCountFrequency (%)
1042711
 
0.9%
1445411
 
0.9%
2651931
 
0.9%
2741751
 
0.9%
2787932
1.7%
2806193
2.6%
2906861
 
0.9%
3150611
 
0.9%
3153801
 
0.9%
3213641
 
0.9%
ValueCountFrequency (%)
4100861
0.9%
4080341
0.9%
3972472
1.7%
3952351
0.9%
3946271
0.9%
3940451
0.9%
3933812
1.7%
3930602
1.7%
3927521
0.9%
3926792
1.7%

_embedded.show.externals.imdb
Categorical

HIGH CORRELATION
MISSING

Distinct31
Distinct (%)57.4%
Missing62
Missing (%)53.4%
Memory size1.0 KiB
tt13599000
tt13486136
tt15561200
 
3
tt3230854
 
3
tt13492362
 
3
Other values (26)
31 

Length

Max length10
Median length10
Mean length9.666666667
Min length9

Characters and Unicode

Total characters522
Distinct characters11
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)38.9%

Sample

1st rowtt13695606
2nd rowtt13470370
3rd rowtt13470370
4th rowtt11492320
5th rowtt9780442

Common Values

ValueCountFrequency (%)
tt135990008
 
6.9%
tt134861366
 
5.2%
tt155612003
 
2.6%
tt32308543
 
2.6%
tt134923623
 
2.6%
tt135397102
 
1.7%
tt135688762
 
1.7%
tt17148102
 
1.7%
tt134703702
 
1.7%
tt135989882
 
1.7%
Other values (21)21
 
18.1%
(Missing)62
53.4%

Length

2022-09-04T23:40:36.530559image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
tt135990008
 
14.8%
tt134861366
 
11.1%
tt155612003
 
5.6%
tt32308543
 
5.6%
tt134923623
 
5.6%
tt135397102
 
3.7%
tt135688762
 
3.7%
tt17148102
 
3.7%
tt134703702
 
3.7%
tt135989882
 
3.7%
Other values (21)21
38.9%

Most occurring characters

ValueCountFrequency (%)
t108
20.7%
167
12.8%
059
11.3%
351
9.8%
641
 
7.9%
938
 
7.3%
838
 
7.3%
436
 
6.9%
534
 
6.5%
229
 
5.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number414
79.3%
Lowercase Letter108
 
20.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
167
16.2%
059
14.3%
351
12.3%
641
9.9%
938
9.2%
838
9.2%
436
8.7%
534
8.2%
229
7.0%
721
 
5.1%
Lowercase Letter
ValueCountFrequency (%)
t108
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common414
79.3%
Latin108
 
20.7%

Most frequent character per script

Common
ValueCountFrequency (%)
167
16.2%
059
14.3%
351
12.3%
641
9.9%
938
9.2%
838
9.2%
436
8.7%
534
8.2%
229
7.0%
721
 
5.1%
Latin
ValueCountFrequency (%)
t108
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII522
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t108
20.7%
167
12.8%
059
11.3%
351
9.8%
641
 
7.9%
938
 
7.3%
838
 
7.3%
436
 
6.9%
534
 
6.5%
229
 
5.6%

_embedded.show.image.medium
Categorical

HIGH CARDINALITY
HIGH CORRELATION
MISSING

Distinct68
Distinct (%)60.7%
Missing4
Missing (%)3.4%
Memory size1.0 KiB
https://static.tvmaze.com/uploads/images/medium_portrait/291/729147.jpg
 
8
https://static.tvmaze.com/uploads/images/medium_portrait/291/729458.jpg
 
6
https://static.tvmaze.com/uploads/images/medium_portrait/289/723331.jpg
 
6
https://static.tvmaze.com/uploads/images/medium_portrait/289/723053.jpg
 
6
https://static.tvmaze.com/uploads/images/medium_portrait/289/722897.jpg
 
4
Other values (63)
82 

Length

Max length72
Median length71
Mean length71.03571429
Min length70

Characters and Unicode

Total characters7956
Distinct characters32
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique48 ?
Unique (%)42.9%

Sample

1st rowhttps://static.tvmaze.com/uploads/images/medium_portrait/315/789854.jpg
2nd rowhttps://static.tvmaze.com/uploads/images/medium_portrait/287/719749.jpg
3rd rowhttps://static.tvmaze.com/uploads/images/medium_portrait/287/719749.jpg
4th rowhttps://static.tvmaze.com/uploads/images/medium_portrait/259/648137.jpg
5th rowhttps://static.tvmaze.com/uploads/images/medium_portrait/270/675333.jpg

Common Values

ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/medium_portrait/291/729147.jpg8
 
6.9%
https://static.tvmaze.com/uploads/images/medium_portrait/291/729458.jpg6
 
5.2%
https://static.tvmaze.com/uploads/images/medium_portrait/289/723331.jpg6
 
5.2%
https://static.tvmaze.com/uploads/images/medium_portrait/289/723053.jpg6
 
5.2%
https://static.tvmaze.com/uploads/images/medium_portrait/289/722897.jpg4
 
3.4%
https://static.tvmaze.com/uploads/images/medium_portrait/376/941244.jpg3
 
2.6%
https://static.tvmaze.com/uploads/images/medium_portrait/289/722948.jpg3
 
2.6%
https://static.tvmaze.com/uploads/images/medium_portrait/380/951122.jpg3
 
2.6%
https://static.tvmaze.com/uploads/images/medium_portrait/350/877137.jpg3
 
2.6%
https://static.tvmaze.com/uploads/images/medium_portrait/370/926884.jpg2
 
1.7%
Other values (58)68
58.6%
(Missing)4
 
3.4%

Length

2022-09-04T23:40:36.606640image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/medium_portrait/291/729147.jpg8
 
7.1%
https://static.tvmaze.com/uploads/images/medium_portrait/289/723331.jpg6
 
5.4%
https://static.tvmaze.com/uploads/images/medium_portrait/289/723053.jpg6
 
5.4%
https://static.tvmaze.com/uploads/images/medium_portrait/291/729458.jpg6
 
5.4%
https://static.tvmaze.com/uploads/images/medium_portrait/289/722897.jpg4
 
3.6%
https://static.tvmaze.com/uploads/images/medium_portrait/376/941244.jpg3
 
2.7%
https://static.tvmaze.com/uploads/images/medium_portrait/289/722948.jpg3
 
2.7%
https://static.tvmaze.com/uploads/images/medium_portrait/380/951122.jpg3
 
2.7%
https://static.tvmaze.com/uploads/images/medium_portrait/350/877137.jpg3
 
2.7%
https://static.tvmaze.com/uploads/images/medium_portrait/285/713120.jpg2
 
1.8%
Other values (58)68
60.7%

Most occurring characters

ValueCountFrequency (%)
/784
 
9.9%
t784
 
9.9%
m560
 
7.0%
a560
 
7.0%
p448
 
5.6%
s448
 
5.6%
i448
 
5.6%
.336
 
4.2%
e336
 
4.2%
o336
 
4.2%
Other values (22)2916
36.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter5600
70.4%
Other Punctuation1232
 
15.5%
Decimal Number1012
 
12.7%
Connector Punctuation112
 
1.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t784
14.0%
m560
10.0%
a560
10.0%
p448
 
8.0%
s448
 
8.0%
i448
 
8.0%
e336
 
6.0%
o336
 
6.0%
u224
 
4.0%
r224
 
4.0%
Other values (8)1232
22.0%
Decimal Number
ValueCountFrequency (%)
2154
15.2%
7132
13.0%
8118
11.7%
1114
11.3%
9112
11.1%
3110
10.9%
479
7.8%
569
6.8%
068
6.7%
656
 
5.5%
Other Punctuation
ValueCountFrequency (%)
/784
63.6%
.336
27.3%
:112
 
9.1%
Connector Punctuation
ValueCountFrequency (%)
_112
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin5600
70.4%
Common2356
29.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
t784
14.0%
m560
10.0%
a560
10.0%
p448
 
8.0%
s448
 
8.0%
i448
 
8.0%
e336
 
6.0%
o336
 
6.0%
u224
 
4.0%
r224
 
4.0%
Other values (8)1232
22.0%
Common
ValueCountFrequency (%)
/784
33.3%
.336
14.3%
2154
 
6.5%
7132
 
5.6%
8118
 
5.0%
1114
 
4.8%
9112
 
4.8%
_112
 
4.8%
:112
 
4.8%
3110
 
4.7%
Other values (4)272
 
11.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII7956
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/784
 
9.9%
t784
 
9.9%
m560
 
7.0%
a560
 
7.0%
p448
 
5.6%
s448
 
5.6%
i448
 
5.6%
.336
 
4.2%
e336
 
4.2%
o336
 
4.2%
Other values (22)2916
36.7%

_embedded.show.image.original
Categorical

HIGH CARDINALITY
HIGH CORRELATION
MISSING

Distinct68
Distinct (%)60.7%
Missing4
Missing (%)3.4%
Memory size1.0 KiB
https://static.tvmaze.com/uploads/images/original_untouched/291/729147.jpg
 
8
https://static.tvmaze.com/uploads/images/original_untouched/291/729458.jpg
 
6
https://static.tvmaze.com/uploads/images/original_untouched/289/723331.jpg
 
6
https://static.tvmaze.com/uploads/images/original_untouched/289/723053.jpg
 
6
https://static.tvmaze.com/uploads/images/original_untouched/289/722897.jpg
 
4
Other values (63)
82 

Length

Max length75
Median length74
Mean length74.03571429
Min length73

Characters and Unicode

Total characters8292
Distinct characters33
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique48 ?
Unique (%)42.9%

Sample

1st rowhttps://static.tvmaze.com/uploads/images/original_untouched/315/789854.jpg
2nd rowhttps://static.tvmaze.com/uploads/images/original_untouched/287/719749.jpg
3rd rowhttps://static.tvmaze.com/uploads/images/original_untouched/287/719749.jpg
4th rowhttps://static.tvmaze.com/uploads/images/original_untouched/259/648137.jpg
5th rowhttps://static.tvmaze.com/uploads/images/original_untouched/270/675333.jpg

Common Values

ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/original_untouched/291/729147.jpg8
 
6.9%
https://static.tvmaze.com/uploads/images/original_untouched/291/729458.jpg6
 
5.2%
https://static.tvmaze.com/uploads/images/original_untouched/289/723331.jpg6
 
5.2%
https://static.tvmaze.com/uploads/images/original_untouched/289/723053.jpg6
 
5.2%
https://static.tvmaze.com/uploads/images/original_untouched/289/722897.jpg4
 
3.4%
https://static.tvmaze.com/uploads/images/original_untouched/376/941244.jpg3
 
2.6%
https://static.tvmaze.com/uploads/images/original_untouched/289/722948.jpg3
 
2.6%
https://static.tvmaze.com/uploads/images/original_untouched/380/951122.jpg3
 
2.6%
https://static.tvmaze.com/uploads/images/original_untouched/350/877137.jpg3
 
2.6%
https://static.tvmaze.com/uploads/images/original_untouched/370/926884.jpg2
 
1.7%
Other values (58)68
58.6%
(Missing)4
 
3.4%

Length

2022-09-04T23:40:36.690558image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/original_untouched/291/729147.jpg8
 
7.1%
https://static.tvmaze.com/uploads/images/original_untouched/289/723331.jpg6
 
5.4%
https://static.tvmaze.com/uploads/images/original_untouched/289/723053.jpg6
 
5.4%
https://static.tvmaze.com/uploads/images/original_untouched/291/729458.jpg6
 
5.4%
https://static.tvmaze.com/uploads/images/original_untouched/289/722897.jpg4
 
3.6%
https://static.tvmaze.com/uploads/images/original_untouched/376/941244.jpg3
 
2.7%
https://static.tvmaze.com/uploads/images/original_untouched/289/722948.jpg3
 
2.7%
https://static.tvmaze.com/uploads/images/original_untouched/380/951122.jpg3
 
2.7%
https://static.tvmaze.com/uploads/images/original_untouched/350/877137.jpg3
 
2.7%
https://static.tvmaze.com/uploads/images/original_untouched/285/713120.jpg2
 
1.8%
Other values (58)68
60.7%

Most occurring characters

ValueCountFrequency (%)
/784
 
9.5%
t672
 
8.1%
a560
 
6.8%
s448
 
5.4%
i448
 
5.4%
o448
 
5.4%
p336
 
4.1%
c336
 
4.1%
.336
 
4.1%
g336
 
4.1%
Other values (23)3588
43.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter5936
71.6%
Other Punctuation1232
 
14.9%
Decimal Number1012
 
12.2%
Connector Punctuation112
 
1.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t672
 
11.3%
a560
 
9.4%
s448
 
7.5%
i448
 
7.5%
o448
 
7.5%
p336
 
5.7%
c336
 
5.7%
g336
 
5.7%
m336
 
5.7%
e336
 
5.7%
Other values (9)1680
28.3%
Decimal Number
ValueCountFrequency (%)
2154
15.2%
7132
13.0%
8118
11.7%
1114
11.3%
9112
11.1%
3110
10.9%
479
7.8%
569
6.8%
068
6.7%
656
 
5.5%
Other Punctuation
ValueCountFrequency (%)
/784
63.6%
.336
27.3%
:112
 
9.1%
Connector Punctuation
ValueCountFrequency (%)
_112
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin5936
71.6%
Common2356
 
28.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
t672
 
11.3%
a560
 
9.4%
s448
 
7.5%
i448
 
7.5%
o448
 
7.5%
p336
 
5.7%
c336
 
5.7%
g336
 
5.7%
m336
 
5.7%
e336
 
5.7%
Other values (9)1680
28.3%
Common
ValueCountFrequency (%)
/784
33.3%
.336
14.3%
2154
 
6.5%
7132
 
5.6%
8118
 
5.0%
1114
 
4.8%
:112
 
4.8%
_112
 
4.8%
9112
 
4.8%
3110
 
4.7%
Other values (4)272
 
11.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII8292
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/784
 
9.5%
t672
 
8.1%
a560
 
6.8%
s448
 
5.4%
i448
 
5.4%
o448
 
5.4%
p336
 
4.1%
c336
 
4.1%
.336
 
4.1%
g336
 
4.1%
Other values (23)3588
43.3%

_embedded.show.summary
Categorical

HIGH CARDINALITY
HIGH CORRELATION
MISSING

Distinct61
Distinct (%)58.1%
Missing11
Missing (%)9.5%
Memory size1.0 KiB
<p>A story that follows undercover cop Gan Tian Lei who spent 10 years of his life walking a gray area. After waking up from a serious injury, he restarts his life and tries to solve a case by relying on his lost memories.</p>
<p><b>Anitta: Made in Honório </b>shows, in an unprecedented way, the private life and career of the singer Anitta, icon of funk and pop in Brazil. The show closely follows the controversial and fascinating artist in her intimacy and during the preparation of important shows on different stages around the world. It also shows her on the road and in meetings with her staff, while accumulating two roles: as an artist and entrepreneur.</p>
 
6
<p>Soda Stereo, Café Tacvba, Aterciopelados and others figure in this 50-year history of Latin American rock through dictatorships, disasters and dissent.</p>
 
6
<p>‎Shen Moo, has no idea what adventures she will face. Beauty, is one of the best observers of Internet resources, but soon, in her head creeps the idea that in the universe there are mermaids. It's hard to believe, but for some reason, she can't get it out of her mind. Soon, she will have to take responsibility to prove their existence, otherwise, the dispute with the professor will turn out to be a real failure for the heroine. Together with the rescue team, they went to help the victims in The Xine Bay. Meet Ahn Xin - an athlete, will turn her reality. Unbelievable, but the guy is perceived as a mermaid. Of course, Mu Xin liked it madly, because she found a key witness and will be able to insist on her own. However, the mermaid man does his best to avoid revealing his real world.‎</p>
 
6
<p>For five years, between 1975 to 1980, the Yorkshire Ripper murders cast a dark shadow over the lives of women in the North of England. 13 women were dead and the police seemed incapable of catching the killer. No one felt safe - and every man was a suspect.</p>
 
4
Other values (56)
75 

Length

Max length913
Median length457
Mean length333.7142857
Min length58

Characters and Unicode

Total characters35040
Distinct characters96
Distinct categories14 ?
Distinct scripts4 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique41 ?
Unique (%)39.0%

Sample

1st row<p>A modern adaptation of the classic novel-poem by Nikolai Gogol. The action takes place in our days. Chichikov, an enterprising and not without charm official from Moscow, this time does not buy up dead souls from small-minded provincials, but sells them places in the cemetery next to celebrities. He arrives in the County town of N and quickly makes" big and small " connections there. These bright acquaintances will benefit him and open up new opportunities for personal gain.</p>
2nd row<p>A modern adaptation of the classic novel-poem by Nikolai Gogol. The action takes place in our days. Chichikov, an enterprising and not without charm official from Moscow, this time does not buy up dead souls from small-minded provincials, but sells them places in the cemetery next to celebrities. He arrives in the County town of N and quickly makes" big and small " connections there. These bright acquaintances will benefit him and open up new opportunities for personal gain.</p>
3rd row<p>The pure and cute little devil Nini lives in Room 1031 of Wan Sheng Street Apartment. His roommates are no ordinary people: The lazy and wacky vampire Ira who spends most of his time gaming or watching TV, the unlucky dancer werewolf Vladimir, the serious and old-fashioned angel landlord Lynn and his naive little sister Lily, and many more.<br /><br />What none of them realize is that the power of the demon king is sleeping inside of Nini. With evil forces in hot pursuit, can Nini and his friends head off disaster?</p>
4th row<p>In ancient Shenzhou, humans and demons had been in constant dispute for thousands of years. The demon princess from Tushan, Bai Binglan, and the human Zhang Kuangyun met each other due to a misunderstanding. In order to investigate the enemy country, Bai Binglan became Zhang Kuangyun's companion. As they travel together, Zhang Kuangyun discovers a conspiracy...</p>
5th row<p>One will to create oceans. One will to summon the mulberry fields.<br /><br />One will to slaughter countless devils. One will to eradicate innumerable immortals.<br /><br />Only my will… is eternal.<br /><br />A Will Eternal tells the tale of Bai Xiaochun, an endearing but exasperating young man who is driven primarily by his fear of death and desire to live forever, but who deeply values friendship and family.<br /><br />(Source: Novel Updates)</p>

Common Values

ValueCountFrequency (%)
<p>A story that follows undercover cop Gan Tian Lei who spent 10 years of his life walking a gray area. After waking up from a serious injury, he restarts his life and tries to solve a case by relying on his lost memories.</p>8
 
6.9%
<p><b>Anitta: Made in Honório </b>shows, in an unprecedented way, the private life and career of the singer Anitta, icon of funk and pop in Brazil. The show closely follows the controversial and fascinating artist in her intimacy and during the preparation of important shows on different stages around the world. It also shows her on the road and in meetings with her staff, while accumulating two roles: as an artist and entrepreneur.</p>6
 
5.2%
<p>Soda Stereo, Café Tacvba, Aterciopelados and others figure in this 50-year history of Latin American rock through dictatorships, disasters and dissent.</p>6
 
5.2%
<p>‎Shen Moo, has no idea what adventures she will face. Beauty, is one of the best observers of Internet resources, but soon, in her head creeps the idea that in the universe there are mermaids. It's hard to believe, but for some reason, she can't get it out of her mind. Soon, she will have to take responsibility to prove their existence, otherwise, the dispute with the professor will turn out to be a real failure for the heroine. Together with the rescue team, they went to help the victims in The Xine Bay. Meet Ahn Xin - an athlete, will turn her reality. Unbelievable, but the guy is perceived as a mermaid. Of course, Mu Xin liked it madly, because she found a key witness and will be able to insist on her own. However, the mermaid man does his best to avoid revealing his real world.‎</p>6
 
5.2%
<p>For five years, between 1975 to 1980, the Yorkshire Ripper murders cast a dark shadow over the lives of women in the North of England. 13 women were dead and the police seemed incapable of catching the killer. No one felt safe - and every man was a suspect.</p>4
 
3.4%
<p>Morten shows you how you can make something cool with what you have at home!</p>3
 
2.6%
<p>Free-spirited Tumi always manages to make a mess of things. Can she make it through this holiday family reunion without ruining it completely?</p>3
 
2.6%
<p>Ty Franck and Wes Chatham dive into the development, behind-the-scenes, and easter eggs of Season 5 of <i>The Expanse.</i></p>3
 
2.6%
<p>A thriller set two hundred years in the future, <b>The Expanse</b> follows the case of a missing young woman who brings a hardened detective and a rogue ship's captain together in a race across the solar system to expose the greatest conspiracy in human history.</p>3
 
2.6%
<p>A story that follows a detective in the major crimes division of Nan Xing City Police Department. Together with a woman who has super memory, he upholds the law one case at a time in solving murders, burglaries and bringing down a narcotics manufacturing facility. Jing Chu is a young and capable detective. Due to his repeated merits from cracking big cases, he is promoted to the position of major crimes division vice-captain at Nan Xing city and starts to work alongside his new team. Because of a murder case, he meets Yang Mian Mian, a young woman who possesses a photographic memory. He soon realizes that Mian Mian seems to have a deep connection to his father's mysterious death many years ago. Meanwhile, a famous blogger and a member of an idol girl group die</p>2
 
1.7%
Other values (51)61
52.6%
(Missing)11
 
9.5%

Length

2022-09-04T23:40:36.788558image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
the305
 
5.1%
and210
 
3.5%
a185
 
3.1%
to170
 
2.9%
of166
 
2.8%
in140
 
2.4%
his87
 
1.5%
her60
 
1.0%
with56
 
0.9%
will44
 
0.7%
Other values (1475)4524
76.1%

Most occurring characters

ValueCountFrequency (%)
5834
16.6%
e3304
 
9.4%
a2223
 
6.3%
t2155
 
6.2%
i1982
 
5.7%
o1977
 
5.6%
n1965
 
5.6%
s1786
 
5.1%
r1704
 
4.9%
h1376
 
3.9%
Other values (86)10734
30.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter26314
75.1%
Space Separator5842
 
16.7%
Uppercase Letter1055
 
3.0%
Other Punctuation967
 
2.8%
Math Symbol620
 
1.8%
Decimal Number110
 
0.3%
Dash Punctuation81
 
0.2%
Format24
 
0.1%
Open Punctuation8
 
< 0.1%
Close Punctuation8
 
< 0.1%
Other values (4)11
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e3304
12.6%
a2223
 
8.4%
t2155
 
8.2%
i1982
 
7.5%
o1977
 
7.5%
n1965
 
7.5%
s1786
 
6.8%
r1704
 
6.5%
h1376
 
5.2%
l1017
 
3.9%
Other values (20)6825
25.9%
Uppercase Letter
ValueCountFrequency (%)
S112
 
10.6%
T102
 
9.7%
A91
 
8.6%
M72
 
6.8%
X52
 
4.9%
H51
 
4.8%
W50
 
4.7%
L49
 
4.6%
B45
 
4.3%
C39
 
3.7%
Other values (16)392
37.2%
Other Punctuation
ValueCountFrequency (%)
,362
37.4%
.299
30.9%
/166
17.2%
'59
 
6.1%
"33
 
3.4%
:24
 
2.5%
!12
 
1.2%
?11
 
1.1%
1
 
0.1%
Decimal Number
ValueCountFrequency (%)
031
28.2%
125
22.7%
515
13.6%
211
 
10.0%
88
 
7.3%
98
 
7.3%
76
 
5.5%
36
 
5.5%
Other Letter
ValueCountFrequency (%)
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
Dash Punctuation
ValueCountFrequency (%)
-73
90.1%
7
 
8.6%
1
 
1.2%
Space Separator
ValueCountFrequency (%)
5834
99.9%
 8
 
0.1%
Math Symbol
ValueCountFrequency (%)
>310
50.0%
<310
50.0%
Open Punctuation
ValueCountFrequency (%)
(7
87.5%
[1
 
12.5%
Close Punctuation
ValueCountFrequency (%)
)7
87.5%
]1
 
12.5%
Format
ValueCountFrequency (%)
24
100.0%
Other Symbol
ValueCountFrequency (%)
1
100.0%
Modifier Letter
ValueCountFrequency (%)
1
100.0%
Currency Symbol
ValueCountFrequency (%)
$1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin27369
78.1%
Common7663
 
21.9%
Katakana4
 
< 0.1%
Han4
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e3304
12.1%
a2223
 
8.1%
t2155
 
7.9%
i1982
 
7.2%
o1977
 
7.2%
n1965
 
7.2%
s1786
 
6.5%
r1704
 
6.2%
h1376
 
5.0%
l1017
 
3.7%
Other values (46)7880
28.8%
Common
ValueCountFrequency (%)
5834
76.1%
,362
 
4.7%
>310
 
4.0%
<310
 
4.0%
.299
 
3.9%
/166
 
2.2%
-73
 
1.0%
'59
 
0.8%
"33
 
0.4%
031
 
0.4%
Other values (22)186
 
2.4%
Katakana
ValueCountFrequency (%)
1
25.0%
1
25.0%
1
25.0%
1
25.0%
Han
ValueCountFrequency (%)
1
25.0%
1
25.0%
1
25.0%
1
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII34974
99.8%
Punctuation33
 
0.1%
None23
 
0.1%
Katakana5
 
< 0.1%
CJK4
 
< 0.1%
Dingbats1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5834
16.7%
e3304
 
9.4%
a2223
 
6.4%
t2155
 
6.2%
i1982
 
5.7%
o1977
 
5.7%
n1965
 
5.6%
s1786
 
5.1%
r1704
 
4.9%
h1376
 
3.9%
Other values (67)10668
30.5%
Punctuation
ValueCountFrequency (%)
24
72.7%
7
 
21.2%
1
 
3.0%
1
 
3.0%
None
ValueCountFrequency (%)
 8
34.8%
é7
30.4%
ó6
26.1%
ā1
 
4.3%
å1
 
4.3%
Katakana
ValueCountFrequency (%)
1
20.0%
1
20.0%
1
20.0%
1
20.0%
1
20.0%
Dingbats
ValueCountFrequency (%)
1
100.0%
CJK
ValueCountFrequency (%)
1
25.0%
1
25.0%
1
25.0%
1
25.0%

_embedded.show.updated
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct72
Distinct (%)62.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1637184876
Minimum1608253013
Maximum1662346277
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2022-09-04T23:40:36.884559image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum1608253013
5-th percentile1608671915
Q11612842583
median1643161934
Q31654976411
95-th percentile1661986111
Maximum1662346277
Range54093264
Interquartile range (IQR)42133828

Descriptive statistics

Standard deviation19715355.73
Coefficient of variation (CV)0.01204222933
Kurtosis-1.568446006
Mean1637184876
Median Absolute Deviation (MAD)14440876.5
Skewness-0.3034464707
Sum1.899134456 × 1011
Variance3.886952515 × 1014
MonotonicityNot monotonic
2022-09-04T23:40:36.986692image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
16549764118
 
6.9%
16549774446
 
5.2%
16122976616
 
5.2%
16086719156
 
5.2%
16422453084
 
3.4%
16394004903
 
2.6%
16124799203
 
2.6%
16501625523
 
2.6%
16574900163
 
2.6%
16124781452
 
1.7%
Other values (62)72
62.1%
ValueCountFrequency (%)
16082530132
 
1.7%
16086719156
5.2%
16090607262
 
1.7%
16095351412
 
1.7%
16096897361
 
0.9%
16108903401
 
0.9%
16114368421
 
0.9%
16120078311
 
0.9%
16122976616
5.2%
16123781171
 
0.9%
ValueCountFrequency (%)
16623462771
0.9%
16622756681
0.9%
16622629611
0.9%
16622179311
0.9%
16620501331
0.9%
16620369661
0.9%
16619691591
0.9%
16619595381
0.9%
16618725611
0.9%
16614857291
0.9%

_embedded.show._links.self.href
Categorical

HIGH CARDINALITY
HIGH CORRELATION

Distinct72
Distinct (%)62.1%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
https://api.tvmaze.com/shows/52743
 
8
https://api.tvmaze.com/shows/52780
 
6
https://api.tvmaze.com/shows/52521
 
6
https://api.tvmaze.com/shows/51928
 
6
https://api.tvmaze.com/shows/51994
 
4
Other values (67)
86 

Length

Max length34
Median length34
Mean length33.94827586
Min length33

Characters and Unicode

Total characters3938
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique52 ?
Unique (%)44.8%

Sample

1st rowhttps://api.tvmaze.com/shows/49630
2nd rowhttps://api.tvmaze.com/shows/52316
3rd rowhttps://api.tvmaze.com/shows/52316
4th rowhttps://api.tvmaze.com/shows/48395
5th rowhttps://api.tvmaze.com/shows/49206

Common Values

ValueCountFrequency (%)
https://api.tvmaze.com/shows/527438
 
6.9%
https://api.tvmaze.com/shows/527806
 
5.2%
https://api.tvmaze.com/shows/525216
 
5.2%
https://api.tvmaze.com/shows/519286
 
5.2%
https://api.tvmaze.com/shows/519944
 
3.4%
https://api.tvmaze.com/shows/521103
 
2.6%
https://api.tvmaze.com/shows/524713
 
2.6%
https://api.tvmaze.com/shows/18253
 
2.6%
https://api.tvmaze.com/shows/570303
 
2.6%
https://api.tvmaze.com/shows/525242
 
1.7%
Other values (62)72
62.1%

Length

2022-09-04T23:40:37.076692image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://api.tvmaze.com/shows/527438
 
6.9%
https://api.tvmaze.com/shows/525216
 
5.2%
https://api.tvmaze.com/shows/519286
 
5.2%
https://api.tvmaze.com/shows/527806
 
5.2%
https://api.tvmaze.com/shows/519944
 
3.4%
https://api.tvmaze.com/shows/521103
 
2.6%
https://api.tvmaze.com/shows/524713
 
2.6%
https://api.tvmaze.com/shows/18253
 
2.6%
https://api.tvmaze.com/shows/570303
 
2.6%
https://api.tvmaze.com/shows/521082
 
1.7%
Other values (62)72
62.1%

Most occurring characters

ValueCountFrequency (%)
/464
 
11.8%
s348
 
8.8%
t348
 
8.8%
h232
 
5.9%
p232
 
5.9%
a232
 
5.9%
o232
 
5.9%
.232
 
5.9%
m232
 
5.9%
e116
 
2.9%
Other values (16)1270
32.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2552
64.8%
Other Punctuation812
 
20.6%
Decimal Number574
 
14.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
s348
13.6%
t348
13.6%
h232
9.1%
p232
9.1%
a232
9.1%
o232
9.1%
m232
9.1%
e116
 
4.5%
w116
 
4.5%
c116
 
4.5%
Other values (3)348
13.6%
Decimal Number
ValueCountFrequency (%)
5112
19.5%
288
15.3%
466
11.5%
162
10.8%
752
9.1%
045
7.8%
841
 
7.1%
641
 
7.1%
335
 
6.1%
932
 
5.6%
Other Punctuation
ValueCountFrequency (%)
/464
57.1%
.232
28.6%
:116
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin2552
64.8%
Common1386
35.2%

Most frequent character per script

Common
ValueCountFrequency (%)
/464
33.5%
.232
16.7%
:116
 
8.4%
5112
 
8.1%
288
 
6.3%
466
 
4.8%
162
 
4.5%
752
 
3.8%
045
 
3.2%
841
 
3.0%
Other values (3)108
 
7.8%
Latin
ValueCountFrequency (%)
s348
13.6%
t348
13.6%
h232
9.1%
p232
9.1%
a232
9.1%
o232
9.1%
m232
9.1%
e116
 
4.5%
w116
 
4.5%
c116
 
4.5%
Other values (3)348
13.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII3938
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/464
 
11.8%
s348
 
8.8%
t348
 
8.8%
h232
 
5.9%
p232
 
5.9%
a232
 
5.9%
o232
 
5.9%
.232
 
5.9%
m232
 
5.9%
e116
 
2.9%
Other values (16)1270
32.2%

_embedded.show._links.previousepisode.href
Categorical

HIGH CARDINALITY
HIGH CORRELATION

Distinct72
Distinct (%)62.1%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
https://api.tvmaze.com/episodes/1997552
 
8
https://api.tvmaze.com/episodes/1998538
 
6
https://api.tvmaze.com/episodes/1987999
 
6
https://api.tvmaze.com/episodes/1987002
 
6
https://api.tvmaze.com/episodes/1987000
 
4
Other values (67)
86 

Length

Max length39
Median length39
Mean length39
Min length39

Characters and Unicode

Total characters4524
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique52 ?
Unique (%)44.8%

Sample

1st rowhttps://api.tvmaze.com/episodes/2380515
2nd rowhttps://api.tvmaze.com/episodes/1983260
3rd rowhttps://api.tvmaze.com/episodes/1983260
4th rowhttps://api.tvmaze.com/episodes/2280228
5th rowhttps://api.tvmaze.com/episodes/2386129

Common Values

ValueCountFrequency (%)
https://api.tvmaze.com/episodes/19975528
 
6.9%
https://api.tvmaze.com/episodes/19985386
 
5.2%
https://api.tvmaze.com/episodes/19879996
 
5.2%
https://api.tvmaze.com/episodes/19870026
 
5.2%
https://api.tvmaze.com/episodes/19870004
 
3.4%
https://api.tvmaze.com/episodes/22345383
 
2.6%
https://api.tvmaze.com/episodes/20240183
 
2.6%
https://api.tvmaze.com/episodes/21900173
 
2.6%
https://api.tvmaze.com/episodes/21701273
 
2.6%
https://api.tvmaze.com/episodes/19880792
 
1.7%
Other values (62)72
62.1%

Length

2022-09-04T23:40:37.150413image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://api.tvmaze.com/episodes/19975528
 
6.9%
https://api.tvmaze.com/episodes/19879996
 
5.2%
https://api.tvmaze.com/episodes/19870026
 
5.2%
https://api.tvmaze.com/episodes/19985386
 
5.2%
https://api.tvmaze.com/episodes/19870004
 
3.4%
https://api.tvmaze.com/episodes/22345383
 
2.6%
https://api.tvmaze.com/episodes/20240183
 
2.6%
https://api.tvmaze.com/episodes/21900173
 
2.6%
https://api.tvmaze.com/episodes/21701273
 
2.6%
https://api.tvmaze.com/episodes/19762022
 
1.7%
Other values (62)72
62.1%

Most occurring characters

ValueCountFrequency (%)
/464
 
10.3%
p348
 
7.7%
s348
 
7.7%
e348
 
7.7%
t348
 
7.7%
o232
 
5.1%
a232
 
5.1%
i232
 
5.1%
.232
 
5.1%
m232
 
5.1%
Other values (16)1508
33.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2900
64.1%
Other Punctuation812
 
17.9%
Decimal Number812
 
17.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
p348
12.0%
s348
12.0%
e348
12.0%
t348
12.0%
o232
8.0%
a232
8.0%
i232
8.0%
m232
8.0%
h116
 
4.0%
d116
 
4.0%
Other values (3)348
12.0%
Decimal Number
ValueCountFrequency (%)
2131
16.1%
9126
15.5%
1110
13.5%
090
11.1%
778
9.6%
870
8.6%
563
7.8%
363
7.8%
642
 
5.2%
439
 
4.8%
Other Punctuation
ValueCountFrequency (%)
/464
57.1%
.232
28.6%
:116
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin2900
64.1%
Common1624
35.9%

Most frequent character per script

Common
ValueCountFrequency (%)
/464
28.6%
.232
14.3%
2131
 
8.1%
9126
 
7.8%
:116
 
7.1%
1110
 
6.8%
090
 
5.5%
778
 
4.8%
870
 
4.3%
563
 
3.9%
Other values (3)144
 
8.9%
Latin
ValueCountFrequency (%)
p348
12.0%
s348
12.0%
e348
12.0%
t348
12.0%
o232
8.0%
a232
8.0%
i232
8.0%
m232
8.0%
h116
 
4.0%
d116
 
4.0%
Other values (3)348
12.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII4524
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/464
 
10.3%
p348
 
7.7%
s348
 
7.7%
e348
 
7.7%
t348
 
7.7%
o232
 
5.1%
a232
 
5.1%
i232
 
5.1%
.232
 
5.1%
m232
 
5.1%
Other values (16)1508
33.3%

image
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing116
Missing (%)100.0%
Memory size1.0 KiB

_embedded.show.webChannel.country.name
Categorical

HIGH CORRELATION
MISSING

Distinct8
Distinct (%)17.0%
Missing69
Missing (%)59.5%
Memory size1.0 KiB
China
28 
Norway
Russian Federation
Korea, Republic of
United States
Other values (3)

Length

Max length25
Median length5
Mean length7.872340426
Min length5

Characters and Unicode

Total characters370
Distinct characters33
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)6.4%

Sample

1st rowRussian Federation
2nd rowRussian Federation
3rd rowChina
4th rowChina
5th rowChina

Common Values

ValueCountFrequency (%)
China28
24.1%
Norway7
 
6.0%
Russian Federation3
 
2.6%
Korea, Republic of3
 
2.6%
United States3
 
2.6%
Taiwan, Province of China1
 
0.9%
Kazakhstan1
 
0.9%
Brazil1
 
0.9%
(Missing)69
59.5%

Length

2022-09-04T23:40:37.224760image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-04T23:40:37.308759image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
china29
46.8%
norway7
 
11.3%
of4
 
6.5%
russian3
 
4.8%
federation3
 
4.8%
korea3
 
4.8%
republic3
 
4.8%
united3
 
4.8%
states3
 
4.8%
taiwan1
 
1.6%
Other values (3)3
 
4.8%

Most occurring characters

ValueCountFrequency (%)
a54
14.6%
i44
11.9%
n41
11.1%
h30
 
8.1%
C29
 
7.8%
e19
 
5.1%
o18
 
4.9%
r15
 
4.1%
15
 
4.1%
t13
 
3.5%
Other values (23)92
24.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter293
79.2%
Uppercase Letter58
 
15.7%
Space Separator15
 
4.1%
Other Punctuation4
 
1.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a54
18.4%
i44
15.0%
n41
14.0%
h30
10.2%
e19
 
6.5%
o18
 
6.1%
r15
 
5.1%
t13
 
4.4%
s10
 
3.4%
w8
 
2.7%
Other values (11)41
14.0%
Uppercase Letter
ValueCountFrequency (%)
C29
50.0%
N7
 
12.1%
R6
 
10.3%
K4
 
6.9%
S3
 
5.2%
U3
 
5.2%
F3
 
5.2%
T1
 
1.7%
P1
 
1.7%
B1
 
1.7%
Space Separator
ValueCountFrequency (%)
15
100.0%
Other Punctuation
ValueCountFrequency (%)
,4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin351
94.9%
Common19
 
5.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
a54
15.4%
i44
12.5%
n41
11.7%
h30
 
8.5%
C29
 
8.3%
e19
 
5.4%
o18
 
5.1%
r15
 
4.3%
t13
 
3.7%
s10
 
2.8%
Other values (21)78
22.2%
Common
ValueCountFrequency (%)
15
78.9%
,4
 
21.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII370
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a54
14.6%
i44
11.9%
n41
11.1%
h30
 
8.1%
C29
 
7.8%
e19
 
5.1%
o18
 
4.9%
r15
 
4.1%
15
 
4.1%
t13
 
3.5%
Other values (23)92
24.9%

_embedded.show.webChannel.country.code
Categorical

HIGH CORRELATION
MISSING

Distinct8
Distinct (%)17.0%
Missing69
Missing (%)59.5%
Memory size1.0 KiB
CN
28 
NO
RU
KR
US
Other values (3)

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters94
Distinct characters11
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)6.4%

Sample

1st rowRU
2nd rowRU
3rd rowCN
4th rowCN
5th rowCN

Common Values

ValueCountFrequency (%)
CN28
24.1%
NO7
 
6.0%
RU3
 
2.6%
KR3
 
2.6%
US3
 
2.6%
TW1
 
0.9%
KZ1
 
0.9%
BR1
 
0.9%
(Missing)69
59.5%

Length

2022-09-04T23:40:37.381759image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-04T23:40:37.458644image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
cn28
59.6%
no7
 
14.9%
ru3
 
6.4%
kr3
 
6.4%
us3
 
6.4%
tw1
 
2.1%
kz1
 
2.1%
br1
 
2.1%

Most occurring characters

ValueCountFrequency (%)
N35
37.2%
C28
29.8%
O7
 
7.4%
R7
 
7.4%
U6
 
6.4%
K4
 
4.3%
S3
 
3.2%
T1
 
1.1%
W1
 
1.1%
Z1
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter94
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N35
37.2%
C28
29.8%
O7
 
7.4%
R7
 
7.4%
U6
 
6.4%
K4
 
4.3%
S3
 
3.2%
T1
 
1.1%
W1
 
1.1%
Z1
 
1.1%

Most occurring scripts

ValueCountFrequency (%)
Latin94
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N35
37.2%
C28
29.8%
O7
 
7.4%
R7
 
7.4%
U6
 
6.4%
K4
 
4.3%
S3
 
3.2%
T1
 
1.1%
W1
 
1.1%
Z1
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII94
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N35
37.2%
C28
29.8%
O7
 
7.4%
R7
 
7.4%
U6
 
6.4%
K4
 
4.3%
S3
 
3.2%
T1
 
1.1%
W1
 
1.1%
Z1
 
1.1%

_embedded.show.webChannel.country.timezone
Categorical

HIGH CORRELATION
MISSING

Distinct8
Distinct (%)17.0%
Missing69
Missing (%)59.5%
Memory size1.0 KiB
Asia/Shanghai
28 
Europe/Oslo
Asia/Kamchatka
Asia/Seoul
America/New_York
Other values (3)

Length

Max length16
Median length13
Mean length12.78723404
Min length10

Characters and Unicode

Total characters601
Distinct characters31
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)6.4%

Sample

1st rowAsia/Kamchatka
2nd rowAsia/Kamchatka
3rd rowAsia/Shanghai
4th rowAsia/Shanghai
5th rowAsia/Shanghai

Common Values

ValueCountFrequency (%)
Asia/Shanghai28
24.1%
Europe/Oslo7
 
6.0%
Asia/Kamchatka3
 
2.6%
Asia/Seoul3
 
2.6%
America/New_York3
 
2.6%
Asia/Taipei1
 
0.9%
Asia/Qyzylorda1
 
0.9%
America/Noronha1
 
0.9%
(Missing)69
59.5%

Length

2022-09-04T23:40:37.537646image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-04T23:40:37.612576image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
asia/shanghai28
59.6%
europe/oslo7
 
14.9%
asia/kamchatka3
 
6.4%
asia/seoul3
 
6.4%
america/new_york3
 
6.4%
asia/taipei1
 
2.1%
asia/qyzylorda1
 
2.1%
america/noronha1
 
2.1%

Most occurring characters

ValueCountFrequency (%)
a108
18.0%
i70
11.6%
h60
10.0%
/47
 
7.8%
s43
 
7.2%
A40
 
6.7%
S31
 
5.2%
n29
 
4.8%
g28
 
4.7%
o23
 
3.8%
Other values (21)122
20.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter454
75.5%
Uppercase Letter97
 
16.1%
Other Punctuation47
 
7.8%
Connector Punctuation3
 
0.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a108
23.8%
i70
15.4%
h60
13.2%
s43
 
9.5%
n29
 
6.4%
g28
 
6.2%
o23
 
5.1%
e18
 
4.0%
r16
 
3.5%
l11
 
2.4%
Other values (10)48
10.6%
Uppercase Letter
ValueCountFrequency (%)
A40
41.2%
S31
32.0%
O7
 
7.2%
E7
 
7.2%
N4
 
4.1%
K3
 
3.1%
Y3
 
3.1%
T1
 
1.0%
Q1
 
1.0%
Other Punctuation
ValueCountFrequency (%)
/47
100.0%
Connector Punctuation
ValueCountFrequency (%)
_3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin551
91.7%
Common50
 
8.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
a108
19.6%
i70
12.7%
h60
10.9%
s43
 
7.8%
A40
 
7.3%
S31
 
5.6%
n29
 
5.3%
g28
 
5.1%
o23
 
4.2%
e18
 
3.3%
Other values (19)101
18.3%
Common
ValueCountFrequency (%)
/47
94.0%
_3
 
6.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII601
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a108
18.0%
i70
11.6%
h60
10.0%
/47
 
7.8%
s43
 
7.2%
A40
 
6.7%
S31
 
5.2%
n29
 
4.8%
g28
 
4.7%
o23
 
3.8%
Other values (21)122
20.3%

_embedded.show._links.nextepisode.href
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct7
Distinct (%)100.0%
Missing109
Missing (%)94.0%
Memory size1.0 KiB
https://api.tvmaze.com/episodes/2374449
https://api.tvmaze.com/episodes/2383511
https://api.tvmaze.com/episodes/2377389
https://api.tvmaze.com/episodes/2383014
https://api.tvmaze.com/episodes/2371586
Other values (2)

Length

Max length39
Median length39
Mean length39
Min length39

Characters and Unicode

Total characters273
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)100.0%

Sample

1st rowhttps://api.tvmaze.com/episodes/2374449
2nd rowhttps://api.tvmaze.com/episodes/2383511
3rd rowhttps://api.tvmaze.com/episodes/2377389
4th rowhttps://api.tvmaze.com/episodes/2383014
5th rowhttps://api.tvmaze.com/episodes/2371586

Common Values

ValueCountFrequency (%)
https://api.tvmaze.com/episodes/23744491
 
0.9%
https://api.tvmaze.com/episodes/23835111
 
0.9%
https://api.tvmaze.com/episodes/23773891
 
0.9%
https://api.tvmaze.com/episodes/23830141
 
0.9%
https://api.tvmaze.com/episodes/23715861
 
0.9%
https://api.tvmaze.com/episodes/23797021
 
0.9%
https://api.tvmaze.com/episodes/23671071
 
0.9%
(Missing)109
94.0%

Length

2022-09-04T23:40:37.687660image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-04T23:40:37.891839image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
https://api.tvmaze.com/episodes/23744491
14.3%
https://api.tvmaze.com/episodes/23835111
14.3%
https://api.tvmaze.com/episodes/23773891
14.3%
https://api.tvmaze.com/episodes/23830141
14.3%
https://api.tvmaze.com/episodes/23715861
14.3%
https://api.tvmaze.com/episodes/23797021
14.3%
https://api.tvmaze.com/episodes/23671071
14.3%

Most occurring characters

ValueCountFrequency (%)
/28
 
10.3%
p21
 
7.7%
s21
 
7.7%
e21
 
7.7%
t21
 
7.7%
a14
 
5.1%
i14
 
5.1%
.14
 
5.1%
m14
 
5.1%
o14
 
5.1%
Other values (16)91
33.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter175
64.1%
Other Punctuation49
 
17.9%
Decimal Number49
 
17.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
p21
12.0%
s21
12.0%
e21
12.0%
t21
12.0%
a14
8.0%
i14
8.0%
m14
8.0%
o14
8.0%
h7
 
4.0%
d7
 
4.0%
Other values (3)21
12.0%
Decimal Number
ValueCountFrequency (%)
310
20.4%
78
16.3%
28
16.3%
15
10.2%
44
 
8.2%
84
 
8.2%
93
 
6.1%
03
 
6.1%
52
 
4.1%
62
 
4.1%
Other Punctuation
ValueCountFrequency (%)
/28
57.1%
.14
28.6%
:7
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin175
64.1%
Common98
35.9%

Most frequent character per script

Common
ValueCountFrequency (%)
/28
28.6%
.14
14.3%
310
 
10.2%
78
 
8.2%
28
 
8.2%
:7
 
7.1%
15
 
5.1%
44
 
4.1%
84
 
4.1%
93
 
3.1%
Other values (3)7
 
7.1%
Latin
ValueCountFrequency (%)
p21
12.0%
s21
12.0%
e21
12.0%
t21
12.0%
a14
8.0%
i14
8.0%
m14
8.0%
o14
8.0%
h7
 
4.0%
d7
 
4.0%
Other values (3)21
12.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII273
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/28
 
10.3%
p21
 
7.7%
s21
 
7.7%
e21
 
7.7%
t21
 
7.7%
a14
 
5.1%
i14
 
5.1%
.14
 
5.1%
m14
 
5.1%
o14
 
5.1%
Other values (16)91
33.3%

_embedded.show.network.id
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct10
Distinct (%)100.0%
Missing106
Missing (%)91.4%
Infinite0
Infinite (%)0.0%
Mean548.8
Minimum30
Maximum1862
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2022-09-04T23:40:37.986911image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum30
5-th percentile38.55
Q1117
median289.5
Q3486
95-th percentile1837.7
Maximum1862
Range1832
Interquartile range (IQR)369

Descriptive statistics

Standard deviation696.4244874
Coefficient of variation (CV)1.268995057
Kurtosis0.9537278269
Mean548.8
Median Absolute Deviation (MAD)201
Skewness1.559143005
Sum5488
Variance485007.0667
MonotonicityNot monotonic
2022-09-04T23:40:38.054270image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
5141
 
0.9%
491
 
0.9%
18081
 
0.9%
18621
 
0.9%
2051
 
0.9%
3741
 
0.9%
4021
 
0.9%
1121
 
0.9%
301
 
0.9%
1321
 
0.9%
(Missing)106
91.4%
ValueCountFrequency (%)
301
0.9%
491
0.9%
1121
0.9%
1321
0.9%
2051
0.9%
3741
0.9%
4021
0.9%
5141
0.9%
18081
0.9%
18621
0.9%
ValueCountFrequency (%)
18621
0.9%
18081
0.9%
5141
0.9%
4021
0.9%
3741
0.9%
2051
0.9%
1321
0.9%
1121
0.9%
491
0.9%
301
0.9%

_embedded.show.network.name
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct10
Distinct (%)100.0%
Missing106
Missing (%)91.4%
Memory size1.0 KiB
ТВ-3
BBC Three
MBC Masr
AfricaMagic Showcase
NFL Network
Other values (5)

Length

Max length20
Median length11
Mean length9.4
Min length4

Characters and Unicode

Total characters94
Distinct characters45
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10 ?
Unique (%)100.0%

Sample

1st rowТВ-3
2nd rowBBC Three
3rd rowMBC Masr
4th rowAfricaMagic Showcase
5th rowNFL Network

Common Values

ValueCountFrequency (%)
ТВ-31
 
0.9%
BBC Three1
 
0.9%
MBC Masr1
 
0.9%
AfricaMagic Showcase1
 
0.9%
NFL Network1
 
0.9%
TV Globo1
 
0.9%
Новий Канал1
 
0.9%
RTL41
 
0.9%
USA Network1
 
0.9%
Tokyo MX1
 
0.9%
(Missing)106
91.4%

Length

2022-09-04T23:40:38.139412image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-04T23:40:38.244799image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
network2
 
11.1%
tv1
 
5.6%
tokyo1
 
5.6%
usa1
 
5.6%
rtl41
 
5.6%
канал1
 
5.6%
новий1
 
5.6%
globo1
 
5.6%
тв-31
 
5.6%
bbc1
 
5.6%
Other values (7)7
38.9%

Most occurring characters

ValueCountFrequency (%)
8
 
8.5%
o7
 
7.4%
r5
 
5.3%
e5
 
5.3%
T4
 
4.3%
M4
 
4.3%
a4
 
4.3%
N3
 
3.2%
c3
 
3.2%
k3
 
3.2%
Other values (35)48
51.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter51
54.3%
Uppercase Letter32
34.0%
Space Separator8
 
8.5%
Decimal Number2
 
2.1%
Dash Punctuation1
 
1.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o7
13.7%
r5
 
9.8%
e5
 
9.8%
a4
 
7.8%
c3
 
5.9%
k3
 
5.9%
w3
 
5.9%
а2
 
3.9%
t2
 
3.9%
i2
 
3.9%
Other values (13)15
29.4%
Uppercase Letter
ValueCountFrequency (%)
T4
12.5%
M4
12.5%
N3
 
9.4%
B3
 
9.4%
L2
 
6.2%
S2
 
6.2%
A2
 
6.2%
C2
 
6.2%
R1
 
3.1%
U1
 
3.1%
Other values (8)8
25.0%
Decimal Number
ValueCountFrequency (%)
41
50.0%
31
50.0%
Space Separator
ValueCountFrequency (%)
8
100.0%
Dash Punctuation
ValueCountFrequency (%)
-1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin71
75.5%
Cyrillic12
 
12.8%
Common11
 
11.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
o7
 
9.9%
r5
 
7.0%
e5
 
7.0%
T4
 
5.6%
M4
 
5.6%
a4
 
5.6%
N3
 
4.2%
c3
 
4.2%
k3
 
4.2%
B3
 
4.2%
Other values (20)30
42.3%
Cyrillic
ValueCountFrequency (%)
а2
16.7%
о1
8.3%
л1
8.3%
н1
8.3%
К1
8.3%
й1
8.3%
и1
8.3%
в1
8.3%
Т1
8.3%
Н1
8.3%
Common
ValueCountFrequency (%)
8
72.7%
41
 
9.1%
31
 
9.1%
-1
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII82
87.2%
Cyrillic12
 
12.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8
 
9.8%
o7
 
8.5%
r5
 
6.1%
e5
 
6.1%
T4
 
4.9%
M4
 
4.9%
a4
 
4.9%
N3
 
3.7%
c3
 
3.7%
k3
 
3.7%
Other values (24)36
43.9%
Cyrillic
ValueCountFrequency (%)
а2
16.7%
о1
8.3%
л1
8.3%
н1
8.3%
К1
8.3%
й1
8.3%
и1
8.3%
в1
8.3%
Т1
8.3%
Н1
8.3%

_embedded.show.network.country.name
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct9
Distinct (%)90.0%
Missing106
Missing (%)91.4%
Memory size1.0 KiB
United States
Russian Federation
United Kingdom
Egypt
South Africa
Other values (4)

Length

Max length18
Median length12.5
Mean length10.4
Min length5

Characters and Unicode

Total characters104
Distinct characters31
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)80.0%

Sample

1st rowRussian Federation
2nd rowUnited Kingdom
3rd rowEgypt
4th rowSouth Africa
5th rowUnited States

Common Values

ValueCountFrequency (%)
United States2
 
1.7%
Russian Federation1
 
0.9%
United Kingdom1
 
0.9%
Egypt1
 
0.9%
South Africa1
 
0.9%
Brazil1
 
0.9%
Ukraine1
 
0.9%
Netherlands1
 
0.9%
Japan1
 
0.9%
(Missing)106
91.4%

Length

2022-09-04T23:40:38.356343image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-04T23:40:38.455966image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
united3
20.0%
states2
13.3%
russian1
 
6.7%
federation1
 
6.7%
kingdom1
 
6.7%
egypt1
 
6.7%
south1
 
6.7%
africa1
 
6.7%
brazil1
 
6.7%
ukraine1
 
6.7%
Other values (2)2
13.3%

Most occurring characters

ValueCountFrequency (%)
t11
 
10.6%
e10
 
9.6%
a10
 
9.6%
i9
 
8.7%
n9
 
8.7%
d6
 
5.8%
5
 
4.8%
s5
 
4.8%
r5
 
4.8%
U4
 
3.8%
Other values (21)30
28.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter84
80.8%
Uppercase Letter15
 
14.4%
Space Separator5
 
4.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t11
13.1%
e10
11.9%
a10
11.9%
i9
10.7%
n9
10.7%
d6
7.1%
s5
 
6.0%
r5
 
6.0%
o3
 
3.6%
g2
 
2.4%
Other values (10)14
16.7%
Uppercase Letter
ValueCountFrequency (%)
U4
26.7%
S3
20.0%
B1
 
6.7%
N1
 
6.7%
K1
 
6.7%
A1
 
6.7%
E1
 
6.7%
F1
 
6.7%
R1
 
6.7%
J1
 
6.7%
Space Separator
ValueCountFrequency (%)
5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin99
95.2%
Common5
 
4.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
t11
11.1%
e10
 
10.1%
a10
 
10.1%
i9
 
9.1%
n9
 
9.1%
d6
 
6.1%
s5
 
5.1%
r5
 
5.1%
U4
 
4.0%
S3
 
3.0%
Other values (20)27
27.3%
Common
ValueCountFrequency (%)
5
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII104
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t11
 
10.6%
e10
 
9.6%
a10
 
9.6%
i9
 
8.7%
n9
 
8.7%
d6
 
5.8%
5
 
4.8%
s5
 
4.8%
r5
 
4.8%
U4
 
3.8%
Other values (21)30
28.8%

_embedded.show.network.country.code
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct9
Distinct (%)90.0%
Missing106
Missing (%)91.4%
Memory size1.0 KiB
US
RU
GB
EG
ZA
Other values (4)

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters20
Distinct characters12
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)80.0%

Sample

1st rowRU
2nd rowGB
3rd rowEG
4th rowZA
5th rowUS

Common Values

ValueCountFrequency (%)
US2
 
1.7%
RU1
 
0.9%
GB1
 
0.9%
EG1
 
0.9%
ZA1
 
0.9%
BR1
 
0.9%
UA1
 
0.9%
NL1
 
0.9%
JP1
 
0.9%
(Missing)106
91.4%

Length

2022-09-04T23:40:38.552500image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-04T23:40:38.625495image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
us2
20.0%
ru1
10.0%
gb1
10.0%
eg1
10.0%
za1
10.0%
br1
10.0%
ua1
10.0%
nl1
10.0%
jp1
10.0%

Most occurring characters

ValueCountFrequency (%)
U4
20.0%
S2
10.0%
R2
10.0%
G2
10.0%
B2
10.0%
A2
10.0%
E1
 
5.0%
Z1
 
5.0%
N1
 
5.0%
L1
 
5.0%
Other values (2)2
10.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter20
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
U4
20.0%
S2
10.0%
R2
10.0%
G2
10.0%
B2
10.0%
A2
10.0%
E1
 
5.0%
Z1
 
5.0%
N1
 
5.0%
L1
 
5.0%
Other values (2)2
10.0%

Most occurring scripts

ValueCountFrequency (%)
Latin20
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
U4
20.0%
S2
10.0%
R2
10.0%
G2
10.0%
B2
10.0%
A2
10.0%
E1
 
5.0%
Z1
 
5.0%
N1
 
5.0%
L1
 
5.0%
Other values (2)2
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII20
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
U4
20.0%
S2
10.0%
R2
10.0%
G2
10.0%
B2
10.0%
A2
10.0%
E1
 
5.0%
Z1
 
5.0%
N1
 
5.0%
L1
 
5.0%
Other values (2)2
10.0%

_embedded.show.network.country.timezone
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct9
Distinct (%)90.0%
Missing106
Missing (%)91.4%
Memory size1.0 KiB
America/New_York
Asia/Kamchatka
Europe/London
Africa/Cairo
Africa/Johannesburg
Other values (4)

Length

Max length19
Median length15.5
Mean length14.8
Min length10

Characters and Unicode

Total characters148
Distinct characters33
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)80.0%

Sample

1st rowAsia/Kamchatka
2nd rowEurope/London
3rd rowAfrica/Cairo
4th rowAfrica/Johannesburg
5th rowAmerica/New_York

Common Values

ValueCountFrequency (%)
America/New_York2
 
1.7%
Asia/Kamchatka1
 
0.9%
Europe/London1
 
0.9%
Africa/Cairo1
 
0.9%
Africa/Johannesburg1
 
0.9%
America/Noronha1
 
0.9%
Europe/Zaporozhye1
 
0.9%
Europe/Amsterdam1
 
0.9%
Asia/Tokyo1
 
0.9%
(Missing)106
91.4%

Length

2022-09-04T23:40:38.703496image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-04T23:40:38.787390image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
america/new_york2
20.0%
asia/kamchatka1
10.0%
europe/london1
10.0%
africa/cairo1
10.0%
africa/johannesburg1
10.0%
america/noronha1
10.0%
europe/zaporozhye1
10.0%
europe/amsterdam1
10.0%
asia/tokyo1
10.0%

Most occurring characters

ValueCountFrequency (%)
r15
 
10.1%
a15
 
10.1%
o15
 
10.1%
e11
 
7.4%
/10
 
6.8%
A8
 
5.4%
i8
 
5.4%
c6
 
4.1%
m6
 
4.1%
n5
 
3.4%
Other values (23)49
33.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter114
77.0%
Uppercase Letter22
 
14.9%
Other Punctuation10
 
6.8%
Connector Punctuation2
 
1.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
r15
13.2%
a15
13.2%
o15
13.2%
e11
9.6%
i8
 
7.0%
c6
 
5.3%
m6
 
5.3%
n5
 
4.4%
s4
 
3.5%
p4
 
3.5%
Other values (11)25
21.9%
Uppercase Letter
ValueCountFrequency (%)
A8
36.4%
E3
 
13.6%
N3
 
13.6%
Y2
 
9.1%
L1
 
4.5%
K1
 
4.5%
C1
 
4.5%
J1
 
4.5%
Z1
 
4.5%
T1
 
4.5%
Other Punctuation
ValueCountFrequency (%)
/10
100.0%
Connector Punctuation
ValueCountFrequency (%)
_2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin136
91.9%
Common12
 
8.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
r15
 
11.0%
a15
 
11.0%
o15
 
11.0%
e11
 
8.1%
A8
 
5.9%
i8
 
5.9%
c6
 
4.4%
m6
 
4.4%
n5
 
3.7%
s4
 
2.9%
Other values (21)43
31.6%
Common
ValueCountFrequency (%)
/10
83.3%
_2
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII148
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
r15
 
10.1%
a15
 
10.1%
o15
 
10.1%
e11
 
7.4%
/10
 
6.8%
A8
 
5.4%
i8
 
5.4%
c6
 
4.1%
m6
 
4.1%
n5
 
3.4%
Other values (23)49
33.1%

_embedded.show.network.officialSite
Categorical

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)100.0%
Missing115
Missing (%)99.1%
Memory size1.0 KiB
https://www.bbc.co.uk/bbcthree

Length

Max length30
Median length30
Mean length30
Min length30

Characters and Unicode

Total characters30
Distinct characters15
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowhttps://www.bbc.co.uk/bbcthree

Common Values

ValueCountFrequency (%)
https://www.bbc.co.uk/bbcthree1
 
0.9%
(Missing)115
99.1%

Length

2022-09-04T23:40:38.880037image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-04T23:40:38.953043image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
https://www.bbc.co.uk/bbcthree1
100.0%

Most occurring characters

ValueCountFrequency (%)
b4
13.3%
t3
10.0%
/3
10.0%
w3
10.0%
.3
10.0%
c3
10.0%
h2
 
6.7%
e2
 
6.7%
p1
 
3.3%
s1
 
3.3%
Other values (5)5
16.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter23
76.7%
Other Punctuation7
 
23.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
b4
17.4%
t3
13.0%
w3
13.0%
c3
13.0%
h2
8.7%
e2
8.7%
p1
 
4.3%
s1
 
4.3%
o1
 
4.3%
u1
 
4.3%
Other values (2)2
8.7%
Other Punctuation
ValueCountFrequency (%)
/3
42.9%
.3
42.9%
:1
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin23
76.7%
Common7
 
23.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
b4
17.4%
t3
13.0%
w3
13.0%
c3
13.0%
h2
8.7%
e2
8.7%
p1
 
4.3%
s1
 
4.3%
o1
 
4.3%
u1
 
4.3%
Other values (2)2
8.7%
Common
ValueCountFrequency (%)
/3
42.9%
.3
42.9%
:1
 
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII30
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
b4
13.3%
t3
10.0%
/3
10.0%
w3
10.0%
.3
10.0%
c3
10.0%
h2
 
6.7%
e2
 
6.7%
p1
 
3.3%
s1
 
3.3%
Other values (5)5
16.7%

_embedded.show.webChannel
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing116
Missing (%)100.0%
Memory size1.0 KiB

_embedded.show.image
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing116
Missing (%)100.0%
Memory size1.0 KiB

_embedded.show.dvdCountry.name
Categorical

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)100.0%
Missing115
Missing (%)99.1%
Memory size1.0 KiB
Ukraine

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters7
Distinct characters7
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowUkraine

Common Values

ValueCountFrequency (%)
Ukraine1
 
0.9%
(Missing)115
99.1%

Length

2022-09-04T23:40:39.016564image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-04T23:40:39.083697image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
ukraine1
100.0%

Most occurring characters

ValueCountFrequency (%)
U1
14.3%
k1
14.3%
r1
14.3%
a1
14.3%
i1
14.3%
n1
14.3%
e1
14.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter6
85.7%
Uppercase Letter1
 
14.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
k1
16.7%
r1
16.7%
a1
16.7%
i1
16.7%
n1
16.7%
e1
16.7%
Uppercase Letter
ValueCountFrequency (%)
U1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin7
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
U1
14.3%
k1
14.3%
r1
14.3%
a1
14.3%
i1
14.3%
n1
14.3%
e1
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII7
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
U1
14.3%
k1
14.3%
r1
14.3%
a1
14.3%
i1
14.3%
n1
14.3%
e1
14.3%

_embedded.show.dvdCountry.code
Categorical

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)100.0%
Missing115
Missing (%)99.1%
Memory size1.0 KiB
UA

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters2
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowUA

Common Values

ValueCountFrequency (%)
UA1
 
0.9%
(Missing)115
99.1%

Length

2022-09-04T23:40:39.141629image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-04T23:40:39.203701image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
ua1
100.0%

Most occurring characters

ValueCountFrequency (%)
U1
50.0%
A1
50.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter2
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
U1
50.0%
A1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Latin2
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
U1
50.0%
A1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII2
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
U1
50.0%
A1
50.0%

_embedded.show.dvdCountry.timezone
Categorical

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)100.0%
Missing115
Missing (%)99.1%
Memory size1.0 KiB
Europe/Zaporozhye

Length

Max length17
Median length17
Mean length17
Min length17

Characters and Unicode

Total characters17
Distinct characters12
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowEurope/Zaporozhye

Common Values

ValueCountFrequency (%)
Europe/Zaporozhye1
 
0.9%
(Missing)115
99.1%

Length

2022-09-04T23:40:39.260579image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-04T23:40:39.326802image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
europe/zaporozhye1
100.0%

Most occurring characters

ValueCountFrequency (%)
o3
17.6%
r2
11.8%
p2
11.8%
e2
11.8%
E1
 
5.9%
u1
 
5.9%
/1
 
5.9%
Z1
 
5.9%
a1
 
5.9%
z1
 
5.9%
Other values (2)2
11.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter14
82.4%
Uppercase Letter2
 
11.8%
Other Punctuation1
 
5.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o3
21.4%
r2
14.3%
p2
14.3%
e2
14.3%
u1
 
7.1%
a1
 
7.1%
z1
 
7.1%
h1
 
7.1%
y1
 
7.1%
Uppercase Letter
ValueCountFrequency (%)
E1
50.0%
Z1
50.0%
Other Punctuation
ValueCountFrequency (%)
/1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin16
94.1%
Common1
 
5.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
o3
18.8%
r2
12.5%
p2
12.5%
e2
12.5%
E1
 
6.2%
u1
 
6.2%
Z1
 
6.2%
a1
 
6.2%
z1
 
6.2%
h1
 
6.2%
Common
ValueCountFrequency (%)
/1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII17
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o3
17.6%
r2
11.8%
p2
11.8%
e2
11.8%
E1
 
5.9%
u1
 
5.9%
/1
 
5.9%
Z1
 
5.9%
a1
 
5.9%
z1
 
5.9%
Other values (2)2
11.8%

Interactions

2022-09-04T23:40:28.808073image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:40:17.168687image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:40:18.340535image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:40:19.290229image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:40:20.274864image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:40:21.138562image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:40:22.077656image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:40:22.992877image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
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Correlations

2022-09-04T23:40:39.402814image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2022-09-04T23:40:39.649954image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2022-09-04T23:40:39.903668image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2022-09-04T23:40:40.303233image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Missing values

2022-09-04T23:40:30.039344image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2022-09-04T23:40:31.107609image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.
2022-09-04T23:40:31.752716image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

Sample

First rows

idurlnameseasonnumbertypeairdateairtimeairstampruntimesummaryrating.averageimage.mediumimage.original_links.self.href_embedded.show.id_embedded.show.url_embedded.show.name_embedded.show.type_embedded.show.language_embedded.show.genres_embedded.show.status_embedded.show.runtime_embedded.show.averageRuntime_embedded.show.premiered_embedded.show.ended_embedded.show.officialSite_embedded.show.schedule.time_embedded.show.schedule.days_embedded.show.rating.average_embedded.show.weight_embedded.show.network_embedded.show.webChannel.id_embedded.show.webChannel.name_embedded.show.webChannel.country_embedded.show.webChannel.officialSite_embedded.show.dvdCountry_embedded.show.externals.tvrage_embedded.show.externals.thetvdb_embedded.show.externals.imdb_embedded.show.image.medium_embedded.show.image.original_embedded.show.summary_embedded.show.updated_embedded.show._links.self.href_embedded.show._links.previousepisode.hrefimage_embedded.show.webChannel.country.name_embedded.show.webChannel.country.code_embedded.show.webChannel.country.timezone_embedded.show._links.nextepisode.href_embedded.show.network.id_embedded.show.network.name_embedded.show.network.country.name_embedded.show.network.country.code_embedded.show.network.country.timezone_embedded.show.network.officialSite_embedded.show.webChannel_embedded.show.image_embedded.show.dvdCountry.name_embedded.show.dvdCountry.code_embedded.show.dvdCountry.timezone
02179613https://www.tvmaze.com/episodes/2179613/kontakty-1x30-kontakty-v-telefone-ili-makarova-ruslan-belyj-guram-amaran-andrej-beburisvili-sasa-vasКОНТАКТЫ в телефоне Ильи Макарова: Руслан Белый, Гурам Амарян, Андрей Бебуришвили, Саша Ваш130.0regular2020-12-1612:002020-12-16T00:00:00+00:0032.0NoneNaNhttps://static.tvmaze.com/uploads/images/medium_landscape/360/901423.jpghttps://static.tvmaze.com/uploads/images/original_untouched/360/901423.jpghttps://api.tvmaze.com/episodes/217961349630https://www.tvmaze.com/shows/49630/kontaktyКонтактыGame ShowRussian[]Running30.042.02019-04-03Nonehttps://www.youtube.com/playlist?list=PLZ1FUdedsrSJubWkFFh5vKHzawzQk1mYI[Monday]NaN20NaN21.0YouTubeNaNhttps://www.youtube.comNaNNaNNaNNonehttps://static.tvmaze.com/uploads/images/medium_portrait/315/789854.jpghttps://static.tvmaze.com/uploads/images/original_untouched/315/789854.jpgNone1661485729https://api.tvmaze.com/shows/49630https://api.tvmaze.com/episodes/2380515NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
11983259https://www.tvmaze.com/episodes/1983259/mertvye-dusi-1x03-seria-3Серия 313.0regular2020-12-162020-12-16T00:00:00+00:0043.0NoneNaNNaNNaNhttps://api.tvmaze.com/episodes/198325952316https://www.tvmaze.com/shows/52316/mertvye-dusiМёртвые душиScriptedRussian[Comedy]Ended43.043.02020-12-092020-12-16https://www.ivi.ru/watch/mertvyie-dushi-2020[Wednesday]NaN22NaN337.0iviNaNhttps://www.ivi.ru/NaNNaN393060.0Nonehttps://static.tvmaze.com/uploads/images/medium_portrait/287/719749.jpghttps://static.tvmaze.com/uploads/images/original_untouched/287/719749.jpg<p>A modern adaptation of the classic novel-poem by Nikolai Gogol. The action takes place in our days. Chichikov, an enterprising and not without charm official from Moscow, this time does not buy up dead souls from small-minded provincials, but sells them places in the cemetery next to celebrities. He arrives in the County town of N and quickly makes" big and small " connections there. These bright acquaintances will benefit him and open up new opportunities for personal gain.</p>1608253013https://api.tvmaze.com/shows/52316https://api.tvmaze.com/episodes/1983260NaNRussian FederationRUAsia/KamchatkaNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
21983260https://www.tvmaze.com/episodes/1983260/mertvye-dusi-1x04-seria-4Серия 414.0regular2020-12-162020-12-16T00:00:00+00:0043.0NoneNaNNaNNaNhttps://api.tvmaze.com/episodes/198326052316https://www.tvmaze.com/shows/52316/mertvye-dusiМёртвые душиScriptedRussian[Comedy]Ended43.043.02020-12-092020-12-16https://www.ivi.ru/watch/mertvyie-dushi-2020[Wednesday]NaN22NaN337.0iviNaNhttps://www.ivi.ru/NaNNaN393060.0Nonehttps://static.tvmaze.com/uploads/images/medium_portrait/287/719749.jpghttps://static.tvmaze.com/uploads/images/original_untouched/287/719749.jpg<p>A modern adaptation of the classic novel-poem by Nikolai Gogol. The action takes place in our days. Chichikov, an enterprising and not without charm official from Moscow, this time does not buy up dead souls from small-minded provincials, but sells them places in the cemetery next to celebrities. He arrives in the County town of N and quickly makes" big and small " connections there. These bright acquaintances will benefit him and open up new opportunities for personal gain.</p>1608253013https://api.tvmaze.com/shows/52316https://api.tvmaze.com/episodes/1983260NaNRussian FederationRUAsia/KamchatkaNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
31997413https://www.tvmaze.com/episodes/1997413/wan-sheng-jie-2x12-ah-goodbye-friendsAh, Goodbye Friends212.0regular2020-12-1610:002020-12-16T02:00:00+00:004.0NoneNaNNaNNaNhttps://api.tvmaze.com/episodes/199741348395https://www.tvmaze.com/shows/48395/wan-sheng-jieWan Sheng JieAnimationChinese[Comedy, Anime, Supernatural]Running4.04.02020-04-01Nonehttps://v.qq.com/detail/a/awnia0n2erqryf3.html10:00[Wednesday]NaN15NaN104.0Tencent QQNaNhttps://v.qq.com/NaNNaN380207.0Nonehttps://static.tvmaze.com/uploads/images/medium_portrait/259/648137.jpghttps://static.tvmaze.com/uploads/images/original_untouched/259/648137.jpg<p>The pure and cute little devil Nini lives in Room 1031 of Wan Sheng Street Apartment. His roommates are no ordinary people: The lazy and wacky vampire Ira who spends most of his time gaming or watching TV, the unlucky dancer werewolf Vladimir, the serious and old-fashioned angel landlord Lynn and his naive little sister Lily, and many more.<br /><br />What none of them realize is that the power of the demon king is sleeping inside of Nini. With evil forces in hot pursuit, can Nini and his friends head off disaster?</p>1647193542https://api.tvmaze.com/shows/48395https://api.tvmaze.com/episodes/2280228NaNChinaCNAsia/ShanghaiNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
42386107https://www.tvmaze.com/episodes/2386107/xian-feng-jian-yu-lu-1x48-episode-48Episode 48148.0regular2020-12-1610:002020-12-16T02:00:00+00:008.0NoneNaNNaNNaNhttps://api.tvmaze.com/episodes/238610749206https://www.tvmaze.com/shows/49206/xian-feng-jian-yu-luXian Feng Jian Yu LuAnimationChinese[Action, Anime, Fantasy, Supernatural]Running8.07.02020-07-11Nonehttps://v.qq.com/detail/m/mzc00200hc38s5x.html10:00[Wednesday, Saturday]NaN52NaN104.0Tencent QQNaNhttps://v.qq.com/NaNNaN386423.0Nonehttps://static.tvmaze.com/uploads/images/medium_portrait/270/675333.jpghttps://static.tvmaze.com/uploads/images/original_untouched/270/675333.jpg<p>In ancient Shenzhou, humans and demons had been in constant dispute for thousands of years. The demon princess from Tushan, Bai Binglan, and the human Zhang Kuangyun met each other due to a misunderstanding. In order to investigate the enemy country, Bai Binglan became Zhang Kuangyun's companion. As they travel together, Zhang Kuangyun discovers a conspiracy...</p>1662275668https://api.tvmaze.com/shows/49206https://api.tvmaze.com/episodes/2386129NaNChinaCNAsia/ShanghaiNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
52095628https://www.tvmaze.com/episodes/2095628/yi-nian-yong-heng-1x21-episode-21Episode 21121.0regular2020-12-1610:002020-12-16T02:00:00+00:0019.0NoneNaNNaNNaNhttps://api.tvmaze.com/episodes/209562849652https://www.tvmaze.com/shows/49652/yi-nian-yong-hengYi Nian Yong HengAnimationChinese[Comedy, Action, Anime, Fantasy]Running19.019.02020-08-12Nonehttps://v.qq.com/detail/w/ww18u675tfmhas6.html10:00[Wednesday]NaN56NaN104.0Tencent QQNaNhttps://v.qq.com/NaNNaN388680.0tt13695606https://static.tvmaze.com/uploads/images/medium_portrait/267/669816.jpghttps://static.tvmaze.com/uploads/images/original_untouched/267/669816.jpg<p>One will to create oceans. One will to summon the mulberry fields.<br /><br />One will to slaughter countless devils. One will to eradicate innumerable immortals.<br /><br />Only my will… is eternal.<br /><br />A Will Eternal tells the tale of Bai Xiaochun, an endearing but exasperating young man who is driven primarily by his fear of death and desire to live forever, but who deeply values friendship and family.<br /><br />(Source: Novel Updates)</p>1660662594https://api.tvmaze.com/shows/49652https://api.tvmaze.com/episodes/2374448NaNChinaCNAsia/Shanghaihttps://api.tvmaze.com/episodes/2374449NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
62096298https://www.tvmaze.com/episodes/2096298/no-turning-back-romance-1x04-4414.0regular2020-12-162020-12-16T03:00:00+00:0012.0NoneNaNNaNNaNhttps://api.tvmaze.com/episodes/209629855002https://www.tvmaze.com/shows/55002/no-turning-back-romanceNo Turning Back RomanceScriptedKorean[]EndedNaN12.02020-12-082021-01-06None[Tuesday, Wednesday]NaN24NaN30.0Naver TVCastNaNhttps://tv.naver.com/NaNNaNNaNNonehttps://static.tvmaze.com/uploads/images/medium_portrait/319/799196.jpghttps://static.tvmaze.com/uploads/images/original_untouched/319/799196.jpg<p>A teen romance of So Dam, a sixteen-year-old girl, who has never dated before but she receives her first-ever love confession from a mysterious boy. She is looking for the boy who secretly confessed to her while she was asleep on her desk. The clues include a male voice, mango fruit scent and gym uniform. She must piece the puzzle to find that person among the likely candidates that include hot shots Park Ji Hoo, Jeong Han Kyul, and Joo In Hyuk.</p>1621617231https://api.tvmaze.com/shows/55002https://api.tvmaze.com/episodes/2096309NaNKorea, Republic ofKRAsia/SeoulNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
72030020https://www.tvmaze.com/episodes/2030020/dolls-frontline-2x12-episode-12Episode 12212.0regular2020-12-1612:002020-12-16T04:00:00+00:005.0NoneNaNNaNNaNhttps://api.tvmaze.com/episodes/203002045713https://www.tvmaze.com/shows/45713/dolls-frontlineDolls' FrontlineAnimationChinese[Comedy, Anime, Science-Fiction]Ended5.05.02019-07-282020-12-16https://www.bilibili.com/bangumi/media/md2822989512:00[Wednesday]NaN20NaN51.0BilibiliNaNNoneNaNNaN373360.0Nonehttps://static.tvmaze.com/uploads/images/medium_portrait/234/587413.jpghttps://static.tvmaze.com/uploads/images/original_untouched/234/587413.jpg<p>Re-imagines famous firearms as moe girls with machine bodies that are known as T-Dolls.</p>1613086641https://api.tvmaze.com/shows/45713https://api.tvmaze.com/episodes/2030020NaNChinaCNAsia/ShanghaiNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
82066369https://www.tvmaze.com/episodes/2066369/chu-feng-yi-dian-shizi-1x06-episode-6Episode 616.0regular2020-12-162020-12-16T04:00:00+00:0030.0NoneNaNNaNNaNhttps://api.tvmaze.com/episodes/206636954637https://www.tvmaze.com/shows/54637/chu-feng-yi-dian-shiziChu Feng: Yi Dian ShiziAnimationChinese[Action]Ended30.030.02020-11-182021-01-27http://weibo.com/u/6516179447[Wednesday]NaN8NaN118.0YoukuNaNNoneNaNNaN395235.0Nonehttps://static.tvmaze.com/uploads/images/medium_portrait/305/764244.jpghttps://static.tvmaze.com/uploads/images/original_untouched/305/764244.jpg<p>Ordinary high school student Haoxuan Sun was taken hostage in a seemingly robbery and rescued by a girl wearing winged battledress with bee bionics designs. Haoxuan Sun's peaceful life was stirred by the girl – human bioengineering weapon Vanguard Liuli. Discovered that he is the "Son of Eden" wanted by all the great powers, Haoxuan Sun and Liuli have been searching for the truth and fight against the so-called destiny. At the same time, people around Haoxuan Sun, senpai Ye Bai who he has a crash on, his best friend, and many others, were discovered to have a second identities.<br /><br />The new BEE anime is based on the original manga plot. In addition, BEE manga's author Baimao personally joined the production team. The new BEE will also include two subplots entirely new to the viewers.</p>1617983545https://api.tvmaze.com/shows/54637https://api.tvmaze.com/episodes/2066376NaNChinaCNAsia/ShanghaiNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
92071481https://www.tvmaze.com/episodes/2071481/youths-in-the-breeze-1x11-people-from-the-story-03PEOPLE FROM THE STORY #03111.0regular2020-12-162020-12-16T04:00:00+00:007.0NoneNaNNaNNaNhttps://api.tvmaze.com/episodes/207148154762https://www.tvmaze.com/shows/54762/youths-in-the-breezeYouths in the BreezeScriptedChinese[Drama, Fantasy]Ended7.07.02020-12-132020-12-22https://v.youku.com/v_show/id_XNDk4OTUxMzg1Mg==.html?spm=a2hbt.13141534.0.13141534&s=6eefbfbd4befbfbd32ef[Monday, Tuesday, Wednesday, Thursday, Friday, Saturday, Sunday]NaN27NaN118.0YoukuNaNNoneNaNNaN397247.0Nonehttps://static.tvmaze.com/uploads/images/medium_portrait/308/770106.jpghttps://static.tvmaze.com/uploads/images/original_untouched/308/770106.jpg<p>The play consists of three youth stories. "He and Meow": The cat Jiang Xiao Kui and his owner Jiang Qing from the cat kingdom live a happy life. Until Jiang Qing's younger brother Jiang Xia returned home. Xia, who was allergic to cats, and Jiang Xiao Kui, who hated his younger brother, started a battle over sister's favor. "Full-time rival": Xu Tian Yi and Li Shi Lin, who had been at odds for a long time, reunited during the summer sprint training. In the process of competing against each other, their misunderstanding was resolved. Just when the two worked together to enter the team, an accident happened. "The Man in the Story": Yu Sheng, a young man, accidentally discovered that he turned out to be a character in Xu Mo's novel. After learning about the tragic ending of himself and his sister, he came to the real world to fight with the writer in an attempt to change his destiny.</p><p><br /> </p>1618466682https://api.tvmaze.com/shows/54762https://api.tvmaze.com/episodes/2071494NaNChinaCNAsia/ShanghaiNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN

Last rows

idurlnameseasonnumbertypeairdateairtimeairstampruntimesummaryrating.averageimage.mediumimage.original_links.self.href_embedded.show.id_embedded.show.url_embedded.show.name_embedded.show.type_embedded.show.language_embedded.show.genres_embedded.show.status_embedded.show.runtime_embedded.show.averageRuntime_embedded.show.premiered_embedded.show.ended_embedded.show.officialSite_embedded.show.schedule.time_embedded.show.schedule.days_embedded.show.rating.average_embedded.show.weight_embedded.show.network_embedded.show.webChannel.id_embedded.show.webChannel.name_embedded.show.webChannel.country_embedded.show.webChannel.officialSite_embedded.show.dvdCountry_embedded.show.externals.tvrage_embedded.show.externals.thetvdb_embedded.show.externals.imdb_embedded.show.image.medium_embedded.show.image.original_embedded.show.summary_embedded.show.updated_embedded.show._links.self.href_embedded.show._links.previousepisode.hrefimage_embedded.show.webChannel.country.name_embedded.show.webChannel.country.code_embedded.show.webChannel.country.timezone_embedded.show._links.nextepisode.href_embedded.show.network.id_embedded.show.network.name_embedded.show.network.country.name_embedded.show.network.country.code_embedded.show.network.country.timezone_embedded.show.network.officialSite_embedded.show.webChannel_embedded.show.image_embedded.show.dvdCountry.name_embedded.show.dvdCountry.code_embedded.show.dvdCountry.timezone
1061998538https://www.tvmaze.com/episodes/1998538/mermaid-prince-1x24-episode-24Episode 24124.0regular2020-12-1621:002020-12-16T13:00:00+00:0045.0NoneNaNNaNNaNhttps://api.tvmaze.com/episodes/199853852780https://www.tvmaze.com/shows/52780/mermaid-princeMermaid PrinceScriptedChinese[Comedy, Fantasy, Romance]Ended45.045.02020-11-252020-12-16None21:00[Wednesday, Thursday, Friday]NaN23NaN104.0Tencent QQNaNhttps://v.qq.com/NaNNaN392162.0Nonehttps://static.tvmaze.com/uploads/images/medium_portrait/291/729458.jpghttps://static.tvmaze.com/uploads/images/original_untouched/291/729458.jpg<p>‎Shen Moo, has no idea what adventures she will face. Beauty, is one of the best observers of Internet resources, but soon, in her head creeps the idea that in the universe there are mermaids. It's hard to believe, but for some reason, she can't get it out of her mind. Soon, she will have to take responsibility to prove their existence, otherwise, the dispute with the professor will turn out to be a real failure for the heroine. Together with the rescue team, they went to help the victims in The Xine Bay. Meet Ahn Xin - an athlete, will turn her reality. Unbelievable, but the guy is perceived as a mermaid. Of course, Mu Xin liked it madly, because she found a key witness and will be able to insist on her own. However, the mermaid man does his best to avoid revealing his real world.‎</p>1654977444https://api.tvmaze.com/shows/52780https://api.tvmaze.com/episodes/1998538NaNChinaCNAsia/ShanghaiNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
1071984185https://www.tvmaze.com/episodes/1984185/nfl-films-presents-2020-12-16-intensityIntensity202015.0regular2020-12-1608:302020-12-16T13:30:00+00:0030.0NoneNaNNaNNaNhttps://api.tvmaze.com/episodes/19841856441https://www.tvmaze.com/shows/6441/nfl-films-presentsNFL Films PresentsSportsEnglish[]Running30.030.01999-08-23Nonehttp://www.nfl.com/videos/nfl-films-presents08:30[Saturday]NaN28NaN30.0Naver TVCastNaNhttps://tv.naver.com/NaNNaN274175.0tt0211159https://static.tvmaze.com/uploads/images/medium_portrait/406/1016520.jpghttps://static.tvmaze.com/uploads/images/original_untouched/406/1016520.jpg<p><b>NFL Films Presents</b> is devoted to producing commercials, television programs, feature films, and documentaries on the National Football League, as well as other unrelated major events and awards shows. It is currently owned by the NFL and produces most of its videotaped content except its live game coverage, which is handled separately by the individual networks."</p>1651026392https://api.tvmaze.com/shows/6441https://api.tvmaze.com/episodes/2261966NaNKorea, Republic ofKRAsia/SeoulNaN205.0NFL NetworkUnited StatesUSAmerica/New_YorkNoneNaNNaNNaNNaNNaN
1081991536https://www.tvmaze.com/episodes/1991536/conversa-com-bial-4x153-especialistas-em-educacaoEspecialistas em educação4153.0regular2020-12-162020-12-16T14:00:00+00:00NaNNoneNaNNaNNaNhttps://api.tvmaze.com/episodes/199153636813https://www.tvmaze.com/shows/36813/conversa-com-bialConversa com BialTalk ShowPortuguese[]RunningNaN40.02017-05-03Nonehttps://globoplay.globo.com/conversa-com-bial/p/10086/[]NaN6NaN131.0GloboplayNaNNoneNaNNaN326962.0tt6853288https://static.tvmaze.com/uploads/images/medium_portrait/156/390605.jpghttps://static.tvmaze.com/uploads/images/original_untouched/156/390605.jpgNone1648342248https://api.tvmaze.com/shows/36813https://api.tvmaze.com/episodes/2302125NaNBrazilBRAmerica/NoronhaNaN374.0TV GloboBrazilBRAmerica/NoronhaNoneNaNNaNNaNNaNNaN
1092036616https://www.tvmaze.com/episodes/2036616/the-bump-2x62-the-bump-74The Bump 74262.0regular2020-12-1610:002020-12-16T15:00:00+00:0030.0NoneNaNNaNNaNhttps://api.tvmaze.com/episodes/203661644660https://www.tvmaze.com/shows/44660/the-bumpThe BumpTalk ShowEnglish[Sports]Running30.030.02019-10-02Nonehttps://watch.wwe.com/original/WWEs-The-Bump-10741010:00[Wednesday]NaN60NaN15.0WWE NetworkNaNNoneNaNNaN371044.0Nonehttps://static.tvmaze.com/uploads/images/medium_portrait/411/1028717.jpghttps://static.tvmaze.com/uploads/images/original_untouched/411/1028717.jpg<p>WWE's <b>The Bump</b> is unlike any WWE show you've ever seen before, featuring a dynamic cast of hosts--led by Kayla Braxton--and WWE Superstars stopping in weekly, both as in-studio and video call-in guests.</p>1659877842https://api.tvmaze.com/shows/44660https://api.tvmaze.com/episodes/2371592NaNUnited StatesUSAmerica/New_Yorkhttps://api.tvmaze.com/episodes/2371586NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
1101984683https://www.tvmaze.com/episodes/1984683/sj-returns-4x83-episode-83Episode 83483.0regular2020-12-1600:002020-12-16T15:00:00+00:005.0NoneNaNNaNNaNhttps://api.tvmaze.com/episodes/198468352250https://www.tvmaze.com/shows/52250/sj-returnsSJ ReturnsRealityKorean[]Running5.05.02017-10-09Nonehttps://tv.naver.com/sjreturns00:00[Monday, Wednesday, Friday]NaN14NaN30.0Naver TVCastNaNhttps://tv.naver.com/NaNNaN336628.0Nonehttps://static.tvmaze.com/uploads/images/medium_portrait/286/716978.jpghttps://static.tvmaze.com/uploads/images/original_untouched/286/716978.jpg<p>This show will follow Super Junior's everyday life.</p>1613088348https://api.tvmaze.com/shows/52250https://api.tvmaze.com/episodes/2030085NaNKorea, Republic ofKRAsia/SeoulNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
1112192624https://www.tvmaze.com/episodes/2192624/diti-proti-zirok-2x11-vypusk-11-ekaterina-kuhar-evgenij-klopotenko-ana-zaecВыпуск 11 (Екатерина Кухар, Евгений Клопотенко, Яна Заец)211.0regular2020-12-1619:002020-12-16T17:00:00+00:0090.0NoneNaNNaNNaNhttps://api.tvmaze.com/episodes/219262444675https://www.tvmaze.com/shows/44675/diti-proti-zirokДіти проти зірокGame ShowUkrainian[Action, Family]Running90.090.02019-09-25Nonehttps://novy.tv/ua/deti-protiv-zvezd/19:00[Wednesday]NaN21NaN21.0YouTubeNaNhttps://www.youtube.comNaNNaNNaNNonehttps://static.tvmaze.com/uploads/images/medium_portrait/365/913800.jpghttps://static.tvmaze.com/uploads/images/original_untouched/365/913800.jpgNone1640952799https://api.tvmaze.com/shows/44675https://api.tvmaze.com/episodes/2245693NaNNaNNaNNaNNaN402.0Новий КаналUkraineUAEurope/ZaporozhyeNoneNaNNaNUkraineUAEurope/Zaporozhye
1122135011https://www.tvmaze.com/episodes/2135011/dimension-20-7x06-collaboratorsCollaborators76.0regular2020-12-162020-12-16T17:00:00+00:00NaNNoneNaNNaNNaNhttps://api.tvmaze.com/episodes/213501156531https://www.tvmaze.com/shows/56531/dimension-20Dimension 20Game ShowEnglish[Comedy, Adventure, Fantasy]RunningNaNNaN2018-09-12Nonehttps://www.dropout.tv/dimension-2019:00[Wednesday]NaN80NaN311.0DropoutNaNNoneNaNNaN354216.0tt9646546https://static.tvmaze.com/uploads/images/medium_portrait/342/856895.jpghttps://static.tvmaze.com/uploads/images/original_untouched/342/856895.jpg<p>Heed the call of adventure and enter <b>Dimension 20</b> where Game Master Brennan Lee Mulligan, joined by comedians and pro gamers, blends comedy with tabletop RPGs.</p>1661872561https://api.tvmaze.com/shows/56531https://api.tvmaze.com/episodes/2382501NaNUnited StatesUSAmerica/New_YorkNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
1131977414https://www.tvmaze.com/episodes/1977414/goede-tijden-slechte-tijden-31x63-aflevering-6318Aflevering 63183163.0regular2020-12-1620:002020-12-16T19:00:00+00:0023.0NoneNaNhttps://static.tvmaze.com/uploads/images/medium_landscape/288/720707.jpghttps://static.tvmaze.com/uploads/images/original_untouched/288/720707.jpghttps://api.tvmaze.com/episodes/19774142504https://www.tvmaze.com/shows/2504/goede-tijden-slechte-tijdenGoede Tijden, Slechte TijdenScriptedDutch[Drama, Romance]Running23.025.01990-10-01Nonehttp://gtst.nl/#!/20:00[Monday, Tuesday, Wednesday, Thursday]NaN84NaNNaNNaNNaNNaNNaN19056.0104271.0tt0096597https://static.tvmaze.com/uploads/images/medium_portrait/332/830481.jpghttps://static.tvmaze.com/uploads/images/original_untouched/332/830481.jpgNone1662346277https://api.tvmaze.com/shows/2504https://api.tvmaze.com/episodes/2379701NaNNaNNaNNaNhttps://api.tvmaze.com/episodes/2379702112.0RTL4NetherlandsNLEurope/AmsterdamNoneNaNNaNNaNNaNNaN
1141958867https://www.tvmaze.com/episodes/1958867/wwe-nxt-14x51-main-event-toni-storm-vs-rhea-ripleyMain Event: Toni Storm vs. Rhea Ripley1451.0regular2020-12-1620:002020-12-17T01:00:00+00:00120.0NoneNaNNaNNaNhttps://api.tvmaze.com/episodes/19588672266https://www.tvmaze.com/shows/2266/wwe-nxtWWE NXTSportsEnglish[]Running120.077.02010-02-23Nonehttp://www.wwe.com/inside/networkschedule20:00[Tuesday]7.290NaN15.0WWE NetworkNaNNoneNaN25100.0144541.0tt1601141https://static.tvmaze.com/uploads/images/medium_portrait/401/1002762.jpghttps://static.tvmaze.com/uploads/images/original_untouched/401/1002762.jpg<p>Each Wednesday at 8:00 p.m. ET, WWE Superstars and Divas of tomorrow face off on <b>WWE NXT</b><i>,</i> a one-hour weekly show that features the brightest and best of WWE's rising stars. WWE NXT showcases the Superstars and Divas from WWE's Performance Center as well as appearances from WWE Superstars and Legends in an intimate setting. WWE NXT broadcasts from the state-of-the-art Full Sail LIVE venue on the Full Sail University in campus in Orlando, Florida.</p>1661969159https://api.tvmaze.com/shows/2266https://api.tvmaze.com/episodes/2383154NaNUnited StatesUSAmerica/New_Yorkhttps://api.tvmaze.com/episodes/236710730.0USA NetworkUnited StatesUSAmerica/New_YorkNoneNaNNaNNaNNaNNaN
1151945146https://www.tvmaze.com/episodes/1945146/noblesse-1x11-lord-lost-childLord / Lost Child111.0regular2020-12-1600:002020-12-17T05:00:00+00:0025.0<p>After being summoned by Lord Raskreia, Seira headed to her hometown of Lukedonia. Raskreia finds out about the false reports to protect Raizel and decides to punish Seira and Gejutel. Meanwhile, Raizel, Frankenstein, and Regis arrive in Lukedonia to save Seira and Gejutel.</p>NaNhttps://static.tvmaze.com/uploads/images/medium_landscape/292/732073.jpghttps://static.tvmaze.com/uploads/images/original_untouched/292/732073.jpghttps://api.tvmaze.com/episodes/194514649732https://www.tvmaze.com/shows/49732/noblesseNoblesseAnimationJapanese[Anime, Supernatural]Ended25.025.02015-12-042020-12-30https://noblesse-anime.com/00:00[Wednesday]NaN44NaN20.0CrunchyrollNaNNoneNaNNaN386818.0Nonehttps://static.tvmaze.com/uploads/images/medium_portrait/268/670751.jpghttps://static.tvmaze.com/uploads/images/original_untouched/268/670751.jpg<p>Raizel awakens from his 820-year slumber. He holds the special title of Noblesse, a pure-blooded Noble and protector of all other Nobles. In an attempt to protect Raizel, his servant Frankenstein enrolls him at Ye Ran High School, where Raizel learns the simple and quotidian routines of the human world through his classmates. However, the Union, a secret society plotting to take over the world, dispatches modified humans and gradually encroaches on Raizel's life, causing him to wield his mighty power to protect those around him... After 820 years of intrigue, the secrets behind his slumber are finally revealed, and Raizel's absolute protection as the Noblesse begins!</p>1648716882https://api.tvmaze.com/shows/49732https://api.tvmaze.com/episodes/1985214NaNNaNNaNNaNNaN132.0Tokyo MXJapanJPAsia/TokyoNoneNaNNaNNaNNaNNaN